WO2014118788A2 - Système d'alerte précoce et/ou de surveillance optique d'une population d'élevage comprenant de la volaille - Google Patents

Système d'alerte précoce et/ou de surveillance optique d'une population d'élevage comprenant de la volaille Download PDF

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Publication number
WO2014118788A2
WO2014118788A2 PCT/IL2014/050122 IL2014050122W WO2014118788A2 WO 2014118788 A2 WO2014118788 A2 WO 2014118788A2 IL 2014050122 W IL2014050122 W IL 2014050122W WO 2014118788 A2 WO2014118788 A2 WO 2014118788A2
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WIPO (PCT)
Prior art keywords
behavior
individuals
animal
tracking
flock
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PCT/IL2014/050122
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English (en)
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WO2014118788A3 (fr
Inventor
Ron Elazari-Volcani
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Faunus Ltd.
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Publication of WO2014118788A2 publication Critical patent/WO2014118788A2/fr
Publication of WO2014118788A3 publication Critical patent/WO2014118788A3/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K29/00—Other apparatus for animal husbandry
    • A01K29/005—Monitoring or measuring activity, e.g. detecting heat or mating
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1112—Global tracking of patients, e.g. by using GPS
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2503/00—Evaluating a particular growth phase or type of persons or animals
    • A61B2503/40—Animals

Definitions

  • the present invention in some embodiments thereof, relates to a system and method for early prediction of and/or early detection condition affecting a livestock population and, more particularly, but not exclusively, to a system for early detection, characterization and/or prediction of epidemics, environmental problems, stress and/or another conditions affecting a livestock population based on remote measurements of behavior changes of individuals in the population.
  • the present invention in some embodiments thereof, relates to a method and system for monitoring a condition of a livestock group and, more particularly, but not exclusively, to a system for monitoring a group of poultry by optical monitoring of a sample of individual from the group.
  • U.S. Patent Application Publication No. 2010/0198024 to Elazari-Volcani et al. discloses a vitality sensing electronic system and method for monitoring the health of a livestock group, comprising: a vitality sensing unit attached to a sample of individual sentinels in a group of livestock, the unit configured to measure a plurality of physiological and behavioral parameters indicative of the sentinel's health condition, location means configured to locate each of the individual sentinels and a computing and storage unit communicating with the vitality sensing unit adapted to determine the group's health based on the sample of measured parameters.
  • U.S. Patent No. 8,297,231 to Yanai et al. discloses a system and method for tracking the health of a group of livestock.
  • the vital signs of a small number of sentinel animals is tracked and used to assess the existence and/or progress of a disease in the group.
  • the vital signs are assessed using a vitality sensor, for example, an accelerometer which provides signals indicating the type and/or other properties of movements made by the sentinel animals.
  • U.S. Patent No. 8,066,179 to Araki et al. discloses methods and systems for monitoring a herd of animals.
  • Each of multiple sensors are attached to one of the animals and is in peer-to-peer communication with another of the sensors to define a dynamically network arrangement of sensors.
  • a base station is in communication with at least one of the sensors to access the networked arrangement of sensors.
  • a central system is in communication with the base station and has instructions to monitor a position of the herd with data collected by the sensors.
  • United States Patent Application 2002/0010390 to Guice et al. discloses a method and system (i.e., an Automated Animal Health Monitoring System— AAHMS) for automated monitoring and early warning of changes in parameters related to the health and status of animals.
  • the system includes implantable wireless "smart tele- sensor" elements that can be implanted within the animal where they measure, and may transmit, temperature and other parameters (e.g., blood oxygen, accelerations, vibrations, heart rate) related to the health and status of the animal being monitored.
  • Optional relay elements may comprise simple transponders to boost the signals from the smart sensor elements and retransmit processed results.
  • the system includes devices for alerting personnel responsible for care of the animals and identifying the animal needing attention.
  • Installation tools include optional capabilities to program the smart sensor elements to adapt to animal type, season, diet, or other user needs, and to read and correlate electronic and machine read data with human readable animal identification (e.g., ear or collar tags).
  • European Patent Application No. EP1212939 discloses a farm management system of a farm for monitoring animals.
  • the system is provided with a computer with an input for supplying the identity of at least one animal.
  • the farm management system is further provided with a plurality of video cameras which are connected with the computer for transmitting image signals to the computer.
  • the cameras are arranged such that at least one animal can be observed at any position of a predetermined area of the farm where the at least one animal can go by at least one camera of the cameras.
  • the computer is arranged to process the image signals of the cameras in combination for monitoring the at least one animal in the area on the basis of the image of the animal itself, distinctly from any other animals which are located in the area.
  • U.S. Patent No. 5,983,837 discloses a bird counter capable of separating, detecting, and counting birds.
  • a counterrotating rotor mechanism having flexible fingers receives the birds into a space between the rotors substantially one at a time to separate the birds.
  • the counterrotating rotor mechanism expels the birds from the space substantially one at a time.
  • a fiber optic bird detecting system detects the number of expelled birds after the birds have been separated by the counterrotating rotors.
  • EP1219170 discloses a method for documenting the state of health of farm animals comprising computer-controlled noninvasive evaluation of their appearance, neurophysiological and neuromuscular condition using standard acoustic, optical, mechanical, tactile, neurophysiological or electrical stimulation. The data produced is then stored. An Independent claim is included for device for carrying out the method.
  • European Patent No. EP0808567 discloses a data-logging apparatus for fitting to an animal, said apparatus comprising sensing means for sensing one or more conditions or activities of the animal, processing means arranged to process output signals from said sensing means and to store data relating to said one or more activities or conditions, and timing means to control the instant of time at which said processing means commences and/or ceases to operate.
  • European Patent No. EP0624313 discloses a method and apparatus for automatically observing the behavior of animals using at least one automatic identification unit.
  • the identification unit can be mounted at several places in a space where domestic animals are housed, for instance the entrance of the milk parlor, a feeding station or a drinking unit. Thus the number of visits of an animal to a milk parlor, feeding station and drinking unit can be registered. At the same time, it is possible to register the time and the duration of each visit. Behavioral patterns can be recorded. By means of analysis software, deviations in the individual animal- specific pattern can be signaled and pronouncements can be made about deviations in the sphere of animal health and fertility. Optical flow, flock behaviour and chicken welfare by Dawkins et al.
  • Dawkins published in Animal Behaviour 2012 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. doi: 10.1016/j.anbehav.2012.04.036 teaches with respect to chickens that due to a lack of "the ability to sift and analyse the vast quantities of data that can now be collected, the information revolution that the new technology promises is incomplete". Particularly, Dawkins states that "large numbers of animals (35 000 in each house),” and because chickens are “homogeneous in appearance (making individual tracking computationally very difficult),” and because poultry "could not be visually marked ... could not be pit-tagged or fitted with loggers".
  • IMS Integrated Management Systems
  • VOA visual image analysis
  • the system uses video cameras placed inside the poultry house, and allows the continuous collection of images. By measuring bird area and length, bird body weight and carcass yield may be determined with an accuracy similar to that of conventional tables (Penz-Jr A.M., Figueiredo, A.N. and Bruno, D.G. (2009) Proceedings, Conferencia Facta de Ciencia e Tecnologia Avicola, 27.).
  • This technique is already used for pigs in Europe, and prediction measures for broilers are still under study because the feathers make the true measure of meat surface area difficult (Green D.M. and Parsons D.J. (2006) Mechanistic Modelling in Pig and Poultry Production (eds R. Gous, T. Morris and C. Fisher), Cab International, 305-321).
  • Chinese published patent application no. CN101894220 (A)- Livestock/poultry health condition data acquisition system discloses a real-time livestock/poultry health condition data acquisition system, which cons of a visual identification platform, a health information database and a sensor network. The entire system has a pyramid structure.
  • the sensor network of the system is arranged on the bottom layer of the system, comprises a pedometer node, a multi-angle camera, a sound sensor node and an environment sensor node, and records breeding environment data and the data of livestock/poultry movement quantity, shape and stress voice
  • the health information database is arranged on a middle layer, and stores behavior and body features of the livestock/poultry at different growth periods
  • the virtual identification platform is arranged on a top layer, and is used for identifying and displaying such as health, sub- health, illness and the like on line according to the breeding environment, and sending system has the advantages of flexible structure, convenient use, capability of well ensuring health growth production benefits and reduction in disease spreading risk.
  • Additional background art includes Chinese published patent application no. CN1464466 (A)- Animal behavior video analyzing system; International Patent Application Publication No. WO2012154841 (A2)- IMAGE ANALYSIS FOR DETERMINING CHARACTERISTICS OF ANIMAL AND HUMANS; Chinese published patent application no. CN101431596 (A)- Dead chicken detection system and detection method for hennery; International Patent Application Publication No. WO2011120529 (Al)- MODEL FOR CLASSIFYING AN ACTIVITY OF AN ANIMAL; Chinese published patent application no. CN 102521400 (A)- Method and system for automatically processing massive data in livestock; and Chinese utility model no. CN202068839 (U)- Intelligent poultry farm management system.
  • a system for monitoring of a condition of a population of livestock including a plurality of markings for indicating members of a sample of sentinels from the population. Some of the markings may be non-distinctive.
  • One or more optical sensors may be configured for tracking a plurality of individuals from the sentinels over time.
  • a processor may be configured for assessing changes in a behavior of each of the individuals and determining a health state of the individuals based on the changes, and extrapolating to determine a health state of the population.
  • a system for monitoring of a condition of a population of livestock including a plurality of markings for indicating members of a sample of sentinels from the population.
  • the system may also include at least one zone wherein the sentinels are not individually identifiable.
  • the system may further include one or more optical sensors configured for tracking a plurality of individuals from the sentinels over time in the zone where sentinels are not individually identifiable.
  • the system may also include a processor.
  • the processor may be configured for assessing changes in a behavior of each of the individuals and determining a health state of the individuals based on the changes, and extrapolating to determine a health state of the population.
  • the behavior includes at least one item selected from the group consisting of walking, running, flying, drinking, eating, sleeping, preening, standing, sitting, lying and eating.
  • the changes include a change is at least one measure selected from the group a portion of time involved in the behavior, an average session length for the behavior, an average rest length between sessions of the behavior, and an intensity of the behavior.
  • the markings include a color that does not disturb the livestock.
  • the marking include at least one member of the group consisting of an IR color, a narrow band reflector, and a fluorescent marking, a marker distinguishable using a narrow band filter.
  • the livestock are bred to be optically distinguishable.
  • the system may further include an orientation mark configured for placement on at least one of the sentinels.
  • the markings are refreshed.
  • the refreshing may includes marking a first group, subsequently marking a second group, simultaneously tracking the first and second group, and continuing tracking the second group after a significant portion of the marks on the first group become unrecognizable.
  • the sensors are further configured to detect a symptom of a disease.
  • the system may further include a non-optical identifier.
  • the non-optical identifier may include at least one device selected from the group consisting of an RFID, a coded LED and a radio transmitter.
  • the system may further include a resolution enhancer.
  • the optical sensors are configured for the tracking without activation of the resolution enhancer and wherein activation of the resolution enhancer decreases a probability of non-distinguishable sentinels by at least one half.
  • the resolution enhancer includes at least one device selected from the group consisting of an optical detector having a higher resolution than the optical sensors, a visible spectrum light source, a non-visible spectrum light source, a narrow band light source, and an optical band filter.
  • the system may further include one or more active beacons configured for mounting on the sentinels.
  • the processor is further configured to track an unidentified sentinel, storing behavior data in a temporary file and integrate the temporary file with a sentinel file upon recognition of the unidentified sentinel.
  • the system may further include at least one zone wherein the individual can be individually identified.
  • the processor is further configured to track an unidentified sentinel, storing behavior data in a temporary file and integrate the temporary file with a sentinel file upon recognition of the unidentified sentinel.
  • a method for monitoring of a condition of a population of livestock may include marking a sample of sentinels from the population; tracking a behavior of a plurality of individuals from the sentinels over time; assessing changes in the behaviors; detecting a health state of the individuals, and tracking a previously identified individual when the individual cannot be directly identified.
  • the tracking includes tracking by means of an optical sensor.
  • the method may further include extrapolating the health state of the individuals to determine a health state of the population.
  • the method may further include refreshing the markings.
  • the method may further include re-identifying a lost sentinel.
  • a strap for mounting a device to an animal including a long belt; a short belt, and a release mechanism for the short belt.
  • the release mechanism may be configured to release the short belt when the animal grows and the long belt may be configured to hold the device to the animal after the animal has grown.
  • the strap may further include a further release mechanism for the entire strap.
  • the release mechanism is by at least one action selected from the group consisting of a remote command, deterioration of the material over time, breaking due to distending as the animal grows, a timed release mechanism.
  • the system may include an optical marking that is not visible to the livestock, and an optical sensor for sensing the marking.
  • the marking includes at least one indicator selected from the group consisting of an IR visible coloring, a fluorescent coloring, an active beacon, a narrow band coloring, a narrow field reflector, and a narrow band reflector.
  • the senor includes at least on element selected from the group consisting of an IR sensor, a UV sensor, and a sensor including a band pass filter.
  • the system may further include a selective illumination source, the selective illumination source may include at least one element is selected from the group consisting of an IR illumination source, a UV illumination source, a narrow band illumination source, a narrow field illumination source, an illumination source including a band pass filter and a short burst illumination source.
  • the system may further include a processor configured for tracking a sample of the livestock marked with the marking, the tracking limited to maximum number of individuals and determining a status of the sample from data derived by from the tracking.
  • the processor is further configured for extrapolating to assess a status of a population larger than the maximum number of individuals based on the data derived from tracking the sample of less than the maximum number.
  • a method of tracking individual animals in a livestock group may include marking the individuals with an optical marking; identifying each the individual; tracking each the individual with an optical sensor; and adjusting the tracking when one or more of the individuals are lost.
  • the adjusting includes improving the tracking in order to avoid further animals from being lost.
  • the adjusting includes at least one action selected from the group consisting of searching for the lost individuals by recognizing the marking with an optical enhanced resolution apparatus, search for the lost individuals using a non-optical marking, mark and track a new individual, continue tracking remaining individuals and count the missing individuals as sick and continue tracking remaining individuals, count missing individuals at reduced weight, adjust weighting of remaining animals to account for change in sampled population and count the missing individuals as healthy.
  • the adjusting includes searching for the lost individuals by recognizing the marking with an optical enhanced resolution apparatus and wherein the recognizing includes at least one element selected from the group consisting of lighting an active beacon, inducing fluorescence in a fluorescent marking, providing an addition source of visible light, providing an addition source of visible light, providing an addition source of UV light, providing an addition source of IR light, providing an addition source of UV light, making an image with a higher resolution sensor.
  • a method of tracking individual animals in a livestock group may include marking the individuals with an optical marking; identifying each the individual; tracking each the individual with an optical sensor, and adjusting the tracking when an identity of two or more of the individuals are confused.
  • the adjusting includes at least one action selected from the group consisting of identifying at least one of the confused individuals by recognizing the marking with the sensor, identifying at least one of the confused individuals by recognizing the marking with an optical enhanced resolution apparatus, identifying at least one of the confused individuals by using a non-optical marking, mark and track a new individual, identifying at least one of the confused individuals by according to a behavior, ascribing to the confused individuals an adjusted behavior, weighting an analysis of the behavior according to an uncertainty of the identity, updating an uncertainty of the identity and continue tracking the confused individuals without counting the confused individuals.
  • the adjusting includes identifying at least one of the confused individuals by recognizing the marking with an optical enhanced resolution apparatus and wherein the recognizing includes at least one element selected from the group consisting of lighting an active beacon, inducing fluorescence in a fluorescent marking, providing an addition source of visible light, providing an addition source of visible light, providing an addition source of UV light, providing an addition source of IR light, providing an addition source of UV light, making an image with a higher record sensor.
  • the adjusting includes tracking incompletely identified individuals and weighting interpretation of observations according to an uncertainty of identification and expected behavior of candidate identities.
  • a method of monitoring a status of livestock may include tracking an individual of the livestock when the individual is not directly identifiable, and detecting a change in a behavior of the individual.
  • the change is relative to a group of the livestock.
  • the detecting includes re- identifying a lost individual.
  • the detecting accounts for an uncertainty in identity of the animal by weighting a significance of the change.
  • the tracking includes making an optical image and analyzing the image.
  • the livestock includes at least one animal selected from the group consisting of a sheep, a goat, a chicken, a poultry, a turkey, a duck, a goose, a chicken, a pheasant, and a fish.
  • the method or system is used for monitoring the health of the population of livestock, evaluate the effectiveness of a health intervention, evaluate side effects of a health intervention, and select breeding stock.
  • a method of early detection of a condition in a population of livestock including: monitoring over time changes in a behavior within the population, and recognizing in the changes a pattern associated with the upcoming condition.
  • a system for early detection of a condition in a population of livestock including: a sensor configured for monitoring over time changes in a behavior within the population, and a computing and storage device configured for recognizing a pattern of the changes associated with the upcoming condition.
  • the computing and storage device includes a memory for storing the pattern.
  • the monitoring occurs while population is apparently healthy.
  • the changes do not include clinical symptoms of the condition.
  • the invention may further include predicting an outbreak of the condition based on the recognizing.
  • the pattern includes a repetition of the behavior.
  • the pattern includes spreading of the behavior to different animals.
  • a time length of the pattern increases over time.
  • the pattern includes spatial spread of the behavior.
  • the pattern includes an increasing difference of the behavior from a normal behavior.
  • the behavior is a measurement of activity.
  • the measurement is a quantification of movements.
  • the movements include non- locomotive movements.
  • the monitoring is of identified individual animals.
  • the invention may further include computing a ranking of the individual within a sample with regards to the behavior and wherein the detecting includes detecting a change is the ranking.
  • the individuals make up a sample of the population.
  • the sample is broken into a plurality of subsamples, and the recognizing is done separately for each subsample.
  • the sample is less than 20% of the population.
  • the invention may further include monitoring a spatial location of the behaviors and wherein the recognizing is further dependent on the location.
  • the livestock includes at least one animal selected from the group consisting of sheep, goats, fish in a fishpond, and poultry in a poultry house, fish in a fishpond, sheep and goats.
  • the condition includes a disease outbreak.
  • the condition includes a stress. According to some embodiments of the invention, the condition includes an interface problem.
  • the behavior includes an aberration from a normal behavior.
  • the condition includes an environmental condition.
  • the pattern includes rising and subsiding of a prevalence of the behavior.
  • the invention may further include analyzing the changes for the presence of the pattern.
  • the invention may further include alerting a caretaker of the state in real time.
  • the pattern includes a reoccurring behavior.
  • a method of estimating vitality of a flock of livestock including: observing movements, including movements while the animal remains in one place, of each of a plurality of individuals in the flock; quantifying the movements; characterizing a respective vitality of each of the individuals from the energy output, and extrapolating from the respective vitality characterizations to estimate the vitality of the flock.
  • a system for estimating vitality of a flock of livestock including: a sensor configured for observing movements, including movements while the animal remains in one place, of each of a plurality of individuals in the flock , and a computing and storage device configured for quantifying the movements; characterizing a respective vitality of each of the individuals from the energy output, and extrapolating from the respective vitality characterizations to estimate the vitality of the flock.
  • the quantifying includes estimating an energy expended.
  • the estimating accounts for a state of the animal.
  • the state includes at least one status selected from the group consisting of a location with respect to a feeder, a location with respect to a water source, walking, sleeping, a time of day, an environmental condition, a status of the plurality of individuals, and a status of the flock.
  • the invention may further include mounting a respective accelerometer on the each individual, and wherein the observing includes summing movements measured by the respective accelerometer.
  • the invention may further include monitoring a second behavior and wherein the characterizing is further based on the monitoring.
  • the invention may further include tracking a second behavior and wherein the characterizing is further based on the tracking.
  • a method of estimating vitality of a flock of livestock including: delineate a virtual flock that is a subset of the flock; characterize a health state of the virtual flock; and extrapolate to the flock.
  • a system for estimating vitality of a flock of livestock including: markings to delineate a virtual flock that is a subset of the flock, and a computing and storage unit configured for: characterizing a health state of the virtual flock and extrapolating to the flock.
  • the invention may further include identifying a vitality of the each individual in the virtual flock and wherein the characterizing is a result of the identifying.
  • the invention may further include alerting a caretaker of a condition, and wherein the alerting further includes informing the caretaker of at least one secondary aspect of the alert, the secondary aspect including at least one attribute selected from the list included of a certainty level of the alert, an acuteness level of the alert, and a potential severity level of the alert.
  • a method of estimating vitality of a flock of livestock including: monitoring a characteristic of each of a group of individuals from the flock; measuring a rate of change of each of the individuals with regard to the characteristic wherein the change is at least partially balanced off within the overall population, and identifying a transmission of a pathology within the flock from a result of the measuring.
  • the vitality is used to select an animal for breeding.
  • the vitality is used for evaluating a health intervention.
  • the vitality is used for comparing at least two groups of animals.
  • the vitality is used for evaluating an environmental condition.
  • a method of estimating vitality of a flock of livestock including: identifying a current state of each individual of a plurality of individuals making up a portion of the flock; recording an observation of a respective individual of the individuals according to his current state; characterizing a respective vitality of the respective individual according to the activity state and the recorded observation, and extrapolating the health state of the plurality of individuals to estimate the vitality of the flock.
  • a system for estimating vitality of a flock of livestock including: a sensor configured for identifying a current state of each individual of a plurality of individuals making up a portion of the flock, and a computing and storage unit configured for: recording an observation of a respective individual of the individuals according to his current state; characterizing a respective vitality of the respective individual according to the activity state and the recorded observation, and extrapolating the health state of the plurality of individuals to estimate the vitality of the flock.
  • the invention may further include identifying a vitality of the each individual from a result of the characterizing.
  • the characterizing is based on an accelerometer output.
  • the invention may further include identifying a vitality of the each individual from a result of the characterizing.
  • the invention may further include evaluating the effect of a health intervention based on the characterizing.
  • the invention may further include comparing at least two groups of animals based on the characterizing.
  • the invention may further include evaluating an environmental condition based on the characterizing.
  • Implementation of the method and/or system of embodiments of the invention can involve performing or completing selected tasks manually, automatically, or a combination thereof.
  • several selected tasks could be implemented by hardware, by software or by firmware or by a combination thereof using an operating system.
  • hardware for performing selected tasks according to embodiments of the invention could be implemented as a chip or a circuit.
  • selected tasks according to embodiments of the invention could be implemented as a plurality of software instructions being executed by a computer using any suitable operating system.
  • one or more tasks according to exemplary embodiments of method and/or system as described herein are performed by a data processor, such as a computing platform for executing a plurality of instructions.
  • the data processor includes a volatile memory for storing instructions and/or data and/or a non-volatile storage, for example, a magnetic hard-disk and/or removable media, for storing instructions and/or data.
  • a network connection is provided as well.
  • a display and/or a user input device such as a keyboard or mouse are optionally provided as well.
  • FIG. 1 is a flow chart of interpretation of observed behavior of a virtual flock in accordance with some embodiments of the current invention
  • FIG. 2 is a flowchart illustration of an exemplary embodiment of optical monitoring of poultry in accordance with an embodiment of the present invention
  • FIGS. 3 A and 3B are images (wide angle and zoom respectively), of an exemplary chicken house having marked and unmarked chickens in accordance with an embodiment of the present invention
  • FIG. 3C is a schematic illustration of a few exemplary embodiments of markings on chickens at a food bowl in accordance with an embodiment of the present invention
  • FIG. 4 is a schematic illustration of an exemplary embodiment of tracking a chicken in a chicken house in accordance with an embodiment of the present invention
  • FIGS. 5 A and 5B are views of an exemplary device for mounting a marker on a chicken in accordance with an embodiment of the present invention
  • FIGS. 6A, 6B and 6C are views of exemplary devices for mounting a marker on a chicken in accordance with an embodiment of the present invention
  • FIG. 7 is a flowchart illustration of an exemplary method of refreshing markings in accordance with an embodiment of the present invention.
  • FIG. 8 is a flowchart illustrating an exemplary method of adjusting tracking in reaction to losing of sentinel in accordance with an embodiment of the present invention
  • FIG. 9 is a flowchart illustrating an exemplary method of adjusting tracking in reaction to confusion in the identity of a least two sentinels in accordance with an embodiment of the present invention.
  • FIG. 10 is an illustration of exemplary zones of high and low resolution around a wide angle optical sensor in accordance with an embodiment of the present invention.
  • FIG. 11 is a flow chart illustration of an exemplary method of adjusting for an unidentified sentinel in accordance with an embodiment of the present invention.
  • FIG. 12 is a schematic illustration of a machine for automatically marking an animal in accordance with an embodiment of the present invention.
  • FIG. 13 is a flow chart illustrating an exemplary method for detecting a condition of an animal or group in accordance with an embodiment of the present invention
  • FIG. 14 is a schematic illustration of an example of tracking a healthy chicken in accordance with an embodiment of the present invention.
  • FIG. 15 is a schematic illustration of an example of tracking a healthy chicken in accordance with an embodiment of the present invention.
  • FIGs. 16A-B are schematic illustrations of two exemplary embodiments of behavior changes that may be a precursor to a disease outbreak in accordance with some embodiments of the current invention.
  • FIG. 17A illustrates an exemplary floor plan of a poultry house in accordance with some embodiments of the current invention
  • FIGs. 17B-E show time lapsed schematic views of an exemplary spread of behavior aberrations in the poultry house of Fig. 17A before a disease outbreak in accordance with some embodiments of the current invention
  • FIG. 18A illustrates resulting measurements from the example of Fig. 17B-D in accordance with some embodiments of the current invention
  • FIG. 18B is a chart illustrating an exemplary embodiment to alerting a caretaker according to the data of FIG 18A in accordance with some embodiments of the current invention
  • FIG. 18C is a chart illustrating an exemplary alternative embodiment to alerting a caretaker in accordance with some embodiments of the current invention.
  • FIG. 19 is an illustration of computations to reducing data to shorten transmissions in accordance with some embodiments of the current invention.
  • FIG. 20A illustrates an example of acceleration measurements for a chicken while drinking in accordance with some embodiments of the current invention
  • FIG. 20B an example of acceleration measurements for a chicken while eating (from 1 sec until 400 seconds) and preening (from 400 sec to 600 sec) in accordance with some embodiments of the current invention
  • FIG. 20C illustrates acceleration typical for a chicken while walking in accordance with some embodiments of the current invention
  • FIG. 20D illustrates acceleration typical for a chicken while sleeping in accordance with some embodiments of the current invention
  • FIG. 21 illustrates an example of changes in activity of a twenty four day old chicken over a day in accordance with some embodiments of the current invention
  • FIGs. 22A-B illustrate an example of acceleration measurements (three hour averages) for three healthy chickens and one chicken who becomes sick over a week in accordance with some embodiments of the current invention
  • FIG. 23A illustrates the normalized activity level of an example of a chicken that was exposed to a chronic illness at age of approximately 28 days in accordance with some embodiments of the current invention
  • FIG. 23B illustrates where the chicken of Fig. 23 failed each of 23 tests in accordance with some embodiments of the current invention
  • FIG. 24A illustrates the normalized activity level of an example of a chicken that was exposed to an acute illness at age of approximately 30 days in accordance with some embodiments of the current invention
  • FIG. 24B illustrates where the chicken of Fig. 24A failed each of 23 tests in accordance with some embodiments of the current invention
  • FIG. 25A illustrates the normalized activity level of an example of a chicken that was exposed to an acute illness and recovered at age of approximately 30 days in accordance with some embodiments of the current invention
  • FIG. 25B illustrates where the chicken of Fig. 25A failed each of 23 tests in accordance with some embodiments of the current invention
  • FIG. 26 is a graph of an experimental example of the number of new chickens failing a vitality criterion over time at the beginning of a disease outbreak in accordance with some embodiments of the current invention.
  • FIG. 27A is a graph of an experimental example of the number tests failed over time at the beginning of a disease outbreak in accordance with some embodiments of the current invention.
  • FIG. 27B is a graph of an experimental example of the cumulative number of chickens failing a vitality criterion over time at the beginning of a disease outbreak;
  • FIGs. 28A-C are time lapse graphs showing a change in ranking and/or relative position of an individual chicken over time in accordance with some embodiments of the current invention.
  • FIG. 29 is a box diagram of a system of measuring vitality in accordance with some embodiments of the current invention.
  • a system may monitor behavior of a sample of individual animals and/or interpret behavior to provide early warning of conditions affecting the flock.
  • the present invention in some embodiments thereof, relates to a method and system for monitoring a group of poultry by optical monitoring of a sample of individual from the group.
  • movements of individual animals may be sampled and interpreted to quantify the activity of each individual.
  • Quantifying activity may include, for example, measuring the energy expended by the animal in movements.
  • Quantifying may include, for example, quantifying the total number of movements and the intensity of the movements. Movements may be measured directly, for example by integrating measurements of an accelerometer and/or movements may be estimated using simplified methodologies. Alternatively or additionally, movements may be tracked and/or measured by optical means and/or by means of location tags, for example RFID tags.
  • Movements that are tracked, quantified and/or analyzed include, for example, locomotion and/or small scale movements such as preening, rolling, shaking etc.
  • a system to alert a caretaker to a condition detected in a portion of a population of livestock and its potential affect on the entire population.
  • the alert may include an assessment of the probability that the condition significantly will affect the entire population, an assessment of the significance of the potential effect and/or an assessment of the acuteness of the condition and/or the level of contagiousness.
  • Alerts may be provided before damage or disease is evident to a human observer.
  • the system may warn of an impending disease outbreak before there is a significant increase in mortality (for example before mortality reaches one per thousand).
  • the system may warn of an impending disease break when even a small portion of the flock (for example less than between 1% and 5% of the flock) has been visibly affected.
  • the system may provide a quantitative assessment of the affect of a condition on the group of livestock.
  • the system may quantify how many animals have been affected beyond a certain threshold (for example what portion of a flock has become sick and/or inactive).
  • the assessment may, for example, be based on changes in normal behavior.
  • the system may recognize a pre- curser of a condition before there are clinical symptoms of the condition.
  • the assessment of a condition of the group is based on movement data and/or a quantification of activity.
  • the assessment may be based on movement data measured and/or tracked using an optical sensor.
  • subclinical aberration in behavior that spreads in the populations may be a sign of a developing condition and set off an alert.
  • a transient reduction in activity that occurs in one or more animals and then reoccurs in other animals may be a sign of a developing epidemic.
  • reoccurring events increase in significance.
  • reoccurring events may have increasing time length (for example for individuals affected and/or for the group of affected animals as a whole) and/or increase in the number of animals affected and/or increase in the seriousness of the symptoms.
  • an aberration that sets off an alert may be apparent at a global, local or individual level.
  • a transient decrease in activity may be measured as a decrease in noise level in a bee hive and or a poultry house for a few hours and/or days.
  • a transient decrease in activity may be measured as a decrease in noise level in a certain area of a poultry house for a few hours and/or days.
  • a transient decrease in activity may be measured as a transient decrease in movements of a few individual animals for a few hours and/or days.
  • an aberration in behavior is spreading and/or increasing (for example to more animals and/or to a new area of a poultry house) may set off an alert.
  • some embodiments are in terms of a specific type animal. It is understood that the description is not limited to that particular kind of animal. For example, each example should be considered as applicable optionally to poultry including for example chickens, ducks, geese, turkeys and/or cattle and/or sheep and/or goats and/or fish and/or bees and/or other livestock mutatis mutandis.
  • early detection may be used for conditions that don't result in death or/and are not disease events.
  • some diseases may have reduced production (for instance growth rate of broilers or egg laying rate of layers) but not produce obvious health changes (for example significant deaths and/or clinical signs of a disease).
  • Examples of such conditions may include Mycoplasma infections, some forms of coccidiosis, mild heat and/or cold stress. Early detection and/or treatment of such conditions may increase productivity.
  • aberrations in an animal's behavior may be detected by measuring an animal's activity.
  • Measures of an animal's activity may optionally include tracking how much time the animal spends in certain states. For example, a system may track how much time the animal spends in near a feeding trough and/or a watering trough and/or how much time an animal spends sitting, sleeping, lying down and/or walking and/or eating and/or standing and/or breeding and/or running and/or bathing and/or preening.
  • Measurements may include the amount of movements and/or the intensity of the movements.
  • interpretation of movements may account for a state of the animal and/or the flock at the time of the measurement.
  • the state of the animal may include whether an animal is sleeping or awake, eating, walking, sitting or lying.
  • the state of the animal may include the location of the animal in its pen and/or with relation to food or water sources and/or other animals.
  • Interpretation may optionally take into other conditions such as environmental conditions, location in the poultry house, the age of an animal, the time of year etc.
  • Interpretation of activity levels may optionally include tracking quantities of behavior, absolute changes in behavior and/or changes in behavior with respect to an expected "normal" behavior and/or a flock averaged behavior and/or historical behavior of the individual. For example, a system may track how far and/or how fast an individual animal and or a group of animals move.
  • relative changes in behavior within the group and changes in rank and/or relative position may indicate a disease being to spread among the flock before the condition is apparent from flock statistics.
  • a sample of a large population of animals will be monitor to track a condition of the population.
  • sample of between 100 and 3000 individual animals may be monitored in order to protect a flock.
  • the flock may have for example a population ranging between 10,000 and 100,000 animals.
  • given sample size for example between 250 and 800 animals may be used regardless of the size of the flock.
  • the sample may be a portion of the flock size for example ranging between 0.1% and 10% of the entire flock.
  • the number of animals sampled may be proportional for example to root of the number of animals for example between the square root and the third root.
  • the sample animals may be individually tracked while the population as a whole may remain anonymous.
  • the sample of animals may be treated as a virtual flock and the population statistics may be used to track the condition of the virtual flock and the results extrapolated to the entire population. Results and/or alerts may be available in real time or near real time.
  • data from animals in a restricted geographic area may be interpreted separately.
  • data may be interpreted locally. For example, a small number of animals behaving suspiciously may not be significant in the entire flock, but if the suspicious animals are concentrated in a particularly area, then this may indicate a significant sign of a problem in that particular area.
  • behavior may be sampled in time.
  • acceleration measurements may be taken at a rate of at a rate between 1 per second to 50 per second in each axis.
  • a rate of sampling may be between 5 per second and 30 per second.
  • Measurements may be sampled, for example, reading for a period ranging in length between 1 and 5 seconds and/or less out of a time period ranging for example between 10 and 100 seconds.
  • Results may be averaged over a period of for example between 5 minutes and 6 hours. More particularly, for example, results may be averaged over a period of between 1 minute and 180 minutes. Measurements may be made for the sampling period for example 1 to 24 times a day for each individual animal.
  • the sampling rate may vary.
  • the sampling rate may be higher during the day than at night and/or sampling may be higher for a more active animal and/or sampling may be increased in certain location, for example near a feed station.
  • Measurements may be collected at a central processor a fixed and/or varying times and/or time intervals. For example, data may be collected at time intervals between one minute and three hours and/or even longer intervals for instance all day. Alternatively or additionally may be collected at a central processor after a certain quantity of movements has been detected and/or after a certain quantity of data has been stored.
  • a general characterization of poultry movement it may be enough to sample movements for one second or two seconds or less out of every 10-30 seconds.
  • the same time sampling may be used on all animals in a group to facilitate comparison between animals.
  • Data may be sent to a central processor, for example, once in a period of between 10 and 180 minutes.
  • data may be sent to the server when a certain number of movements have been measured and/or when a certain quantity of data has been stored.
  • periodic measurements may be made to determine a qualitative activity state. For example, a measurement may be for 2 seconds or more once every period of 15 seconds to 5 minutes and the state of the animal during the measuring period may be determined.
  • the animal may be determined if the animal was walking, resting, breeding, lying on its side, lying on its stomach, lying on its back, rolling, cleaning itself, preening, eating and/or drinking.
  • the measurements may be used, for example, to determine what portion and/or what times of the day the animal spends in what activities.
  • some activities may activate an emergency alert. For example if a lot of animals start lying down at an unusual time, an emergency alert may be transmitted warning of a possibility acute heat stroke.
  • aberrations in behavior may be detected by measuring an eating habit, crowding in different areas of an enclosure, crowding around water and/or food sources and/or other significant locations, signs of fighting, social changes in flock.
  • a first antenna located near a feeder and configured to receive signals from animals within a range of for example between 1 cm and 100 cm of the feeder.
  • a system for remote tracking of behavior of individual animals within a population of livestock provides vitality information for use in genetic selection for growing improved poultry. For example, detailed data may be collected from individual animals. This data may optionally be used to choose and/or breed strains for particular purposes. For example a breed that recovers faster from pre-clinical level disease states may be preferred in a place where poultry diseases are a problem. Behavior under particular stresses, for example during viral outbreaks, may optionally be used to breed animals with higher resistance to particular conditions and/or diseases. Animals having more movement may be bred, for example, to achieve a higher muscle to fat ratio. Animals having less movement may be bred to achieve a higher feed utilization rate.
  • animals may be bred to have stronger upper bodies and/or stronger lower bodies and/or legs.
  • animals with stronger lower bodies and/or legs may be healthier and/or more active during breeding.
  • the data may include information about constitution (for example how often an individual or a flock is affected by subclinical disease conditions and/or how quickly they recover). This data may be used, for example, to develop strains with higher resistance to diseases.
  • data may be collected on the rate of development of an animal. For example, a more active animal may develop faster. For example, certain behaviors that indicate developmental state may be tracked.
  • such measures may be used to breed an animal that develops faster and/or is ready for market in a shorter time.
  • stronger and/or more active animals may be selected and bred. It may be possible to grow stronger animals faster and/or more uniformly than weaker animals (which may for example get sick).
  • An aspect of some embodiments of the current invention includes optical tracking of individuals in a virtual flock taken from a large population.
  • changes detected in the individuals may be used to detect and/or predict a present and/or future condition of the virtual flock.
  • the condition of each individual may be determined based on appearance of the animals and/or based on behavior changes with respect to individual history and/or other criteria.
  • epidemiological and/or statistical methodologies may be used detect and/or predict the present and/or future condition of the virtual flock.
  • extrapolation may be used to estimate and/or predict the present and/or future condition of the entire group.
  • detailed statistical information about the status of each individual sentinel may give a detailed account of the status of a virtual flock of sentinels.
  • the status of the virtual flock may optionally be monitored and/or extrapolated to estimate the status of entire population.
  • results of detecting, accounting, tracking, and/or extrapolating his may be available in real time.
  • a population of livestock for example the population of a chicken house may include between 5,000 and 100,000 individuals.
  • the population of commercial chicken house may include between 9,000 and 60,000 individuals.
  • the house may be packed with, for example, 4 to 25 chickens per square meter of space. In some areas of the house (for example around food dispensers) the crowding may be much greater.
  • a virtual flock may include between 100 and 2000 animals. Typically, for example, it may include between 200 and 1000 animals.
  • the virtual flock may be entirely included in a single undivided space and/or the virtual flock may be spread through a few section of a large enclosure.
  • each sentinel may be marked.
  • the markings may be not include a distinctive mark for each individual sentinels. Individual sentinels may be tracked constantly for identification.
  • a sentinel marking may be orientational.
  • an orientation mark may be color coded, for example the head of each sentinel may be marked with one color and the tail with another and/or a mark on the back of each sentinel may be black near the neck and blue near the tail.
  • a orientation mark may be geometric, for example an arrow on a chicken's back pointed towards the chicken's neck and/or a circle may be painted on a chicken's head and a triangle on his back.
  • a subgroup of the sentinels may be marked with a recognizable mark. For instance, some or all of the sentinels may be marked with a first marking and a sub-group of the sentinels may be marked with an alternative or additional marking. Optionally there may be a multiple identifiable subgroups. Some of the subgroups may include only one chicken.
  • a large number of distinctive marks may be used on a larger number of animals.
  • an individual may be distinguished from most of the other individuals by distinctive markings.
  • identity of sentinels may be preserved through constant tracking.
  • the confused sentinels can be, for example, erased from the database and/or tracked without using their previous histories and/or tracked and separated by comparing their current behavior to the known previous behavior of the two sentinels.
  • every individual of the virtual flock may be marked with an individually distinctive mark.
  • Each individual sentinels may optionally be recognized in each measurement (for example in each image) from its mark.
  • marked sentinels may be tracked. Recognition of individual marks may be used when necessary to identify a sentinel when the tracking has failed to clearly identify one or more sentinels.
  • a sentinel may be marked with a general marking common to some or all of the sentinels and an individually distinguishable marker for identification.
  • the general marking may be of a distinct color differentiating it from the individual markings.
  • a marker may be applied to a chicken.
  • a chicken may be painted and/or a portion of the chicken's feathers may be dyed.
  • a marker for example a color coded tag and/or an electronic tag for example an RFID and/or a location device for example a GPS sensor and/or a coded sensor, for example an LED with a coded signal
  • a marker may be mounted to and/or implanted into an animal.
  • a marker mounted to an animal may be configured to remain on the animal as it grows.
  • a marker tied to a chicken's wings may include an elastic belt.
  • a marker tied to a chickens wing's may include two belts. A tight belt that holds on to a chick and is released as the chicken grows and a loose belt that holds the marker on the adult chicken after the tight belt is released.
  • a marker may be released from a chicken automatically and/or remotely when it is no longer needed.
  • a marker may include a beacon to make it easy to find for example when the animal is slaughtered and/or when it falls off the animal.
  • a marker may be removed from an animal by hand.
  • markers may be renewed over time.
  • a mark may be refreshed for example by repainting or replacing. Refreshing may be automated and/or manual.
  • a system may be modified to recognize a marker as it changes.
  • a computer may have a learning algorithm that finds new indicators to recognize an animal as a set of markings change (for example as the fade and/or wear off).
  • a second group of animals may be marked.
  • the second group may be tracked before a significant number of the first group are unrecognizable.
  • background historical data will be collected on the new group before the old group is lost.
  • a sentinel may be marked with an optical marking.
  • An optical marking may, optionally, include a color code and/or pattern to identify an animal.
  • the pattern may be orientation sensitive.
  • the sentinel may have an orientation marking and an orientation sensitive identification pattern.
  • an optical marking may be configured to reduce disruption to animal behavior.
  • the marker may be invisible and/or minimally visible to the animal marked.
  • a bird that is blind to the infrared (IR) spectrum may be marked with an IR marking.
  • the optical sensors may include an IR sensor.
  • a sentinel may be marked with a marker that is not invisible and/or minimally visible under incident lighting.
  • an animal may be marked with a fluorescent marking that becomes visible under, for example strong ultra-violet (UV) radiation.
  • UV ultra-violet
  • an animal may be marked with a color that does not arouse strong behavior aberrations.
  • a filter may be used to make visible marks that are not apparent to the birds themselves.
  • birds with distinctive natural marking may be used for sentinels. For example, between 100 and 2000 spotted chickens may be introduced as sentinels in a house of 9,000-60,000 chickens.
  • a breed of animals may be used wherein each animal has distinctive markings and/or wherein 1-5% of the animals have a particular marking distinguishable from the rest of the flock. For example, one may put one or more genes responsible for certain colors at certain locations on a certain percentage of the poultry. One can cause a selected percentage of birds to have a unique appearance from the rest of the band. 6. Tracking
  • tracking may time and/or location dependent.
  • tracking resolution in time and/or space may differ in some locations and/or times and/or dependent a state of the sentinels. For example, at night when many sentinels are sleeping there may be fewer moving sentinels to track.
  • tracking may use a lower frame rate and/or lower light and/or resolution.
  • near a food dispenser animals may be more densely packed then elsewhere. Near the food dispenser the tracking may use higher frame rate and/or higher resolution imaging and/or improved light conditions.
  • a UV light may be placed near the food dispenser exiting fluorescent tags allowing recognition of sentinels under the more crowded conditions.
  • the conditions near a food dispenser may make it possible to distinguish individual markings of a sentinel, while in another area the conditions may prevent distinguishing individual markings.
  • identification of an individual sentinel may depend on tracking the individual. Alternatively or additionally tracking may be more or less constant over time and/or homogeneous over space.
  • a single area may be covered by multiple cameras at different angles. The multiple cameras making multiple images of the same area may help preserve tracking when an animal is obscured from one view. Multiple angle images may make it possible to monitor a three dimensional trajectory of an animal.
  • the activity of a sentinel may be measured. Measures of a sentinel's activity may optionally include tracking how much time the sentinel spends in certain states. For example, a system may track how much time the animal spends in and/or near a feeding trough and/or a watering trough. For example, a system may track how much time an animal spends sitting, sleeping, and/or lying down and/or resting and/or walking and/or eating and/or standing and/or breeding and/or running and/or bathing and/or preening.
  • Measurements may include the amount of movements and/or the intensity of the movements, for example one or more of the speed of locomotion and/or the amount of food eaten and/or water drunk and/or the altitude of flight.
  • the system may report to a user what portion of a virtual flock is in given state and/or status (for example what portion of the flock is healthy, sick, aberrant, normal, sub-normal, above-normal). For example, the reports may be given on-demand and/or at fixed times and/or constantly and/or in real time.
  • the system may optionally measure locomotion and/or non-locomotive movements. Determining an animal's vitality may optionally include quantifying an amount of energy expended on locomotion and/or on non-locomotive movements.
  • interpretation of movements may account for a state of an animal and/or the flock at the time of the measurement.
  • the state of the animal may include whether an animal is sleeping or awake, eating, walking, standing sitting or lying.
  • the state of the animal may include the location of the animal in its pen and/or with relation to feeders and/or with relation water sources and/or with relation other animals.
  • Interpretation may optionally take into account other factors such as environmental conditions, location in the chicken house, the age of an animal, the time of year, the time of day etc.
  • Interpretation of activity levels may optionally include tracking quantities of behavior, absolute changes in behavior and/or changes in behavior with respect to an expected "normal" behavior and/or a flock averaged behavior and/or historical behavior of the individual. For example, a system may track how far and/or how fast an individual animal and or a group of animals may move.
  • an optical sensor may be used to detect visual symptoms of a condition of a group of animals.
  • optical sensors may be used to detect blood in stools or on the body of an animal.
  • optical sensors may be used to detect un-groomed animals.
  • optical sensors may be used to detect huddling behavior.
  • system or method of the present invention may be used for example for early prediction of epidemics and/or disease break outs and/or other conditions affecting a livestock population.
  • a monitoring system may provide information for use in genetic selection for growing improved poultry.
  • detailed data may be collected from individual animals. This data may optionally be used to choose and/or breed strains for particular purposes. For example a breed that recovers faster from pre-clinical level disease states may be preferred in a place where chicken diseases are a problem. Behavior under particular stresses, for example during viral outbreaks, may optionally be used to breed animals with higher resistance to particular conditions and/or diseases. Chickens having more movement may be bred, for example, to achieve a higher muscle to fat ratio. Chickens having less movement may be bred to achieve a higher feed utilization rate. For example, animals with stronger lower bodies and/or legs may be healthier and/or more active during breeding.
  • the system may be used to develop animals with one or more positive attributes for example hardier, healthier, more active, faster growing, bigger, better adapted to crowded conditions, more efficient feed utilization.
  • a health monitoring system may be used, for example, to estimate the effectiveness of the intervention. For example, this may allow a farmer to change an ineffective intervention. Alternatively or additionally, different interventions may be tried in different sections of the house.
  • the monitoring system may be used for example to determine the most effective intervention.
  • the system can provide data for quality testing of vaccines. For example, chickens may be vaccinated and then given an illness, the system can be used to measure which vaccine in more effective at preventing side effects and/or minor disruption of health and/or welfare. Alternatively or additionally statistics can be accumulated over time to determine which vaccine is most effective at reducing the disruption of a chicken house due to various diseases.
  • the system can give information to help evaluate of the quality of vaccines and the materials used in them, the qualities of various genetic lines of chickens (for example which are more resistant to disease and/or healthier during breeding).
  • vaccines of different companies may be evaluated to determine which vaccination has fewer side effects and/or which and a vaccine more effective preventing side effects during an infection event.
  • An aspect of some embodiments of the current invention includes predicting an outbreak of an epidemic and/or diseases and/or stress and/or other health threats in a population of livestock based on observation of behavior. For example, prior to a clinical outbreak, individuals may show subtle behavior aberrations that may optionally serve as an early warning that the population is in danger. Behavior changes may in some cases be due for example to the infection's spreading among carriers and/or due to low level exposure causing subclinical infections. In some cases a low level infection (for example a viral infection) and/or stress (for example low level cold stress) will be followed by a more serious infection (for example a bacterial infection). For example, the earlier infection and/or stress may reduce the resistance of the population. Optionally, the system may be used for early detection and identification of low level stresses and/or infections that may reduce the productivity of livestock.
  • a low level infection for example a viral infection
  • stress for example low level cold stress
  • the system may be used for early detection and identification of low level stresses and/or infections that may reduce the productivity of livestock
  • a target behavior may be monitored over time. Significant and/or reoccurring and/or spreading and/or increasing frequency and/or increasing intensity and/or increasing variety of behavior changes and/or aberrations may trigger a warning of a possible danger to the population.
  • the behavior may be monitored in all in the population in general and/or in a sample of the population and/or in various subgroups of the population.
  • a method may start by establishing 102 an expected range for a target behavior.
  • the expected range may optionally be dynamic (for example it may changes as an animal grows and/or be dependent on time of year and/or time of time and/or environmental conditions.
  • the expected range may optionally be defined statistically and/or with respect to other animals in the group and/or outside of the group.
  • Expected behavior may optionally be defined for an individual and/or a group of animals.
  • the range may optionally be established on the basis of data available in the literature and/or by means of measurements on the healthy population and/or a healthy portion of the population. The expected behavior may change according to history of measurements.
  • the baseline may periodically be updated.
  • the range may be comparative for instance a ranking within a group of animals and/or the range may apply to a relationship to a group average and/or variance.
  • a sample of animals may be selected 103.
  • the sample may optionally be selected 103 to be representative of the entire group.
  • the sample may optionally include animals mixed throughout the group.
  • the size of the sample may optionally be chosen for example to allow the sample to be treated as a virtual flock and/or to allow meaningful statistic treatment of the sample.
  • the target behavior may be monitored 104.
  • Monitoring 104 may optionally be direct and/or indirect (for example food intake may be measured by observing the number of animals located at a feeder and/or by amount of feed supplied).
  • the monitoring may optionally be of an individual.
  • the food intake of each individual may be monitored 104.
  • the monitoring 104 may be of the group in general.
  • the total food consumption of the population and/or the consumption of food at each of a plurality of feeders may be monitored 104.
  • the strength of individual movements may be monitored 104 and/or the number of movements.
  • the amount of time spent in one or more states for example walking, sitting, grooming, eating, drinking, and/or sleeping) may be monitored 104.
  • data measured by a sensor may be processed 105.
  • data may be processed by a processor at the sensor to reduce storage and/or transmission requirements.
  • data may be processed 105 by a central processor.
  • data may be transmitted 106.
  • data may optionally be transmitted 106 from a sensor to a central processing unit.
  • raw data may be transmitted 106 to a central processor and/or data may be processed 105 before transmission.
  • results of monitoring 104 may be stored 107.
  • Storage 107 may optionally include local storage 107 at a sensor.
  • Storage 107 may optionally include storage 107 by a central processor, for example after transmission 106.
  • monitoring 104 results may be analyzed 108.
  • Analyzing 108 may optionally be prior to and/or after storing the results.
  • Analysis 108 may optionally include detecting significant changes and/or aberrations 110 in the target behavior.
  • detecting changes and/or aberrations 110 may include one or more tests including for example statistical comparisons to past behaviors and/or to stored behavior ranges and/or group behaviors, and/or detecting changes and/or aberrations 110 may include detecting changes in a ranking.
  • analyzing 108 data may optionally include recognizing a reoccurring pattern 112 of behavior changes and/or aberrations. For example, a single animal may repeat a behavior pattern and/or a behavior pattern may occur by one animal and then be repeated by another animal and/or a reoccurring behavior patterns may be recognized in an anonymous group. Optionally, aberrations and/or changes that are not individually significant may take significance due to their repetition.
  • Analyzing 108 behavior may optionally include comparing a measured behavior to a threshold. Analyzing may optionally use statistical tools such as means, standard deviations and the like.
  • the system may optionally test for a highly significant 114 aberration. For example, if the single aberration is not of high enough significance 114 then the system may go back to monitoring.
  • the system may optionally determine 117 the significance to the entire group of animals. For example, more data may be collected about the occurrence of the behavior in the entire group and/or to determine the cause of the behavior and/or whether it may be endanger a significant portion of the flock. For example, if it is found that there is no increase 115 in the incidence of the aberration in the entire flock and/or there is no significant danger to the entire flock, then the system may optionally return to monitoring 104.
  • the system may optionally send an alert 116 to a flock manager.
  • the system may optionally make further tests 118.
  • a veterinarian may be called to examine animals in which aberrations occur.
  • the system may optionally direct the veterinarian to the animal, for example by displaying a map marking of the location of the animal and/or by an active beacon on the animal etc.
  • the system may move to an alert mode in which monitoring 104 is done more intensively.
  • the system may turn on further observation systems, for example cameras and/or chemical sensors.
  • a caretaker and/or a veterinarian and/or an automatic system may start a prophylactic intervention 120.
  • prophylactic intervention 120 may optionally include for example, drug treatment (e.g. putting an antibiotic into the poultry feed) and/or improving the quantity and/or quality of feed and/or changing the temperature of an enclosure where the group is housed (for example by adjusting a heater, a vent, and/or a fan) and/or cleaning an enclosure where the group is housed and/or extermination of pests and/or slaughtering the part or all of the population early and/or other interventions.
  • monitoring 104 and/or further tests 118 may be used to determine the effectiveness 122 of intervention 120.
  • intervention 120 may be adjusted according the results of monitoring 104 and/or testing 118. If the intervention is determined to be effective 122 and the problem has been solved, the system may optionally return to monitoring 104 the group.
  • the effect of heat on livestock may be a function of temperature and humidity, and it may be measured in "heat load units" that take into account the fact that on a humid heat is subjectively harder than a dry heat.
  • a control system (for example for a poultry house) may account for heat and humidity with heat stress or units for convenience effectiveness coop climate control. Behavior may optionally be used to develop a heat humidity control strategy and/or a heat load unit and/or a heat load scale. The scale and/or the control strategy may depend on the type of animal and/or the age. For example chicks may be sensitive to cold. The maximum temperature and/or minimum temperature for chicks may be for example from 1 to 3 degrees Celsius above the temperature that is used for older birds.
  • the livestock enclosure temperature may be set for example between one and three degrees Celsius below the temperature used for a humidity of 50% to 60%. If the humidity will be between 70% to 80 % then the temperature may be set between for example two and four degrees Celsius below temperature used for a humidity of 50% to 60% then the temperature may be set between one and three degrees Celsius above temperature used for a humidity of 50% to 60%.
  • the system may control temperature based on measured temperature and/or humidity and/or may use behavioral and / or biological feedback.
  • Ventilation may be increased.
  • the temperature may be set a bit higher and/or the humidity allowed to increase.
  • heat emissions or behavior indicate heat or cold stress the temperature control system may be adjusted accordingly.
  • Outdoor temperature and/or variations in temperature and/or other conditions around the livestock enclosure may be accounted for.
  • the system may increase the temperature and/or reduce the humidity when a wet floor condition is detected.
  • FIG. 2 is a flow chart illustrating an exemplary embodiment 200 of a method for monitoring a livestock group in accordance with some embodiments of the current invention.
  • the method may optionally begin by marking 202 a sample of the group.
  • the sample may include a virtual flock of sentinels.
  • a sample (for example the virtual flock) may optionally be big enough to analyze 208 using statistical and/or epidemiological methodologies.
  • the size of a sample may depend on the level of confidence desired in prediction and/or detection.
  • the virtual flock may optionally be representative of the flock.
  • the virtual flock may optionally be small enough to allow efficient and/or detailed observation.
  • the system may optionally be initialized 204 by identifying the sentinels (which may for example be mixed within the larger group).
  • observations 205 may be made and recorded 206 for each sentinel and/or for a group of sentinels.
  • the sentinels may be tracked 210 and/or re- identified 211, and then observed 205 again.
  • Analysis 208 may include, for example, comparisons among the sentinels and/or between groups of sentinels and/or of changes over time within the group and/or a subgroup or within the sentinels and/or a subgroup thereof.
  • the markings may become less recognizable (for example due to corruption and/or fading over time, molting, growth of hair and/or feathers etc.).
  • the markings may optionally be refreshed 212, for example by remarking the same animals and/or by freshly marking new animals and/or by the detection system learning to recognized the sentinels using the signs that remain. //. Importance of marking a sample
  • Figs. 3 A and 3B illustrate respective wide and close up views of an enhanced contrast image of an exemplary embodiment 300a of chickens in a chicken house in accordance with some embodiments of the current invention.
  • a crowded chicken house having for example 10-30 chickens per square meter and sometimes much more in particular locations, for example in the vicinity of a feeder
  • a chicken coop may contain a very large number of birds (for example between 10,000 to 60,000). Tracking the location and/or behavior and/or status of such a large number of individuals may require excessive computational resources. For example, in a chicken house of 10,000 to 60,000 birds we may mark between 300-3000 sentinels.
  • An aspect of some embodiments of the present invention is that we select and mark a sample of sentinels from the population that is small enough to allow detailed tracking and/or identification and/or individual analysis.
  • the sample may be large enough to be representing of the entire population using methodologies developed for protecting large populations.
  • FIG. 3A A group of approximately forty birds is illustrated in fig. 3A in accordance with some embodiments of the current invention. Amongst the forty birds there may be for example three marked sentinels 314a-c. Two feeders 322a,b are shown in the image.
  • the image of Figs. 3 A and 3B was made using a wide angle fisheye lens in accordance with some embodiments of the current invention.
  • the lens may allow a single sensor to cover a large area of an enclosure.
  • images of animals in the center of the field of view and close to the lens may be seen clearly with little distortion. Animals towards the edges of the field of view and far from the lens are may appear distorted and small.
  • the sensor was hung over a feeder so that the image of this important zone has a relative high resolution, while zones towards the edges of the chicken house are visible with more distortion and poorer resolution.
  • the sentinels may optionally be identified and/or tracked and/or observed in detail.
  • a detailed history may be optionally stored for each and/or groups of the sentinels (for example 314a-c).
  • each sentinel 314a-c is marked with the same marking.
  • a marking may include a large easily identified mark 316b-c.
  • 316b-c For example on the back of each sentinel 314a-c in embodiment 300a there is a large triangle.
  • one corner of mark 316b-c points to the head of each sentinel 314a- c.
  • each sentinel 314a-c may be marked with an orientation mark.
  • the head of each sentinels 318a-c is marked with an orientation mark 318b-c.
  • Orientation marks 318b-c may help discriminate the head of sentinel 314a-c from the other chickens in the vicinity.
  • Orientation mark 318b-c may also optionally help to distinguish the direction in which sentinel 314a-c is facing.
  • Orientation mark 318b-c may also optionally help to distinguish the activity in which a sentinel 314a-c is involved. For example, in Fig. 3B, from orientation mark 318b we can see that sentinel 314b has his head in a feeder 322b; he is probably eating. If sentinel's 314b head were bent back over his back, it may be sign that he is preening and/or sleeping (with his head near his body for warmth).
  • each chicken may be marked with an individually identifiable mark.
  • each chicken could be marked with a color code and/or a bar code and/or shape.
  • the burden on tracking may be reduced.
  • the sentinel may be re-identified based on the markings.
  • the conditions of the animal house may place constraints on individual markings. For example, there may be a limitation of avoiding certain colors which arouse a pecking behavior. For example, in turkeys, almost any unusual spot with arouse pecking.
  • markings may be colored with colors that are not visible to the birds, for example IR.
  • certain kinds of markings and/or materials may be avoided due to the danger that they will get into food items if they remain (intentionally or unintentionally) on the animals when they are sent to slaughter.
  • the lighting conditions, camera quality and/or degradation of markings over time etc. may limit the ability to distinguish small symbols. This may, for example, limit the number of distinctive marks that may be used.
  • orientation sensitive symbols may increase the number of distinctive marks.
  • orientation sensitive symbols may be used in conjunction with an orientation mark on the chicken. For example the orientation mark may increase the certainty of orientation when reading the mark.
  • Fig. 3C illustrates a schematic view of an exemplary embodiment 300b of chickens at a feeder including some exemplary embodiments of markings in accordance with some embodiments of the current invention.
  • Some embodiments of the current invention may include one or more of the various marking formats illustrated in embodiment 300b.
  • Some embodiments of the current invention may include one or more animals with the same markings and/or one or more animals with different permutations of the same marking format (for example similar geometry markings with different color combinations).
  • Some embodiments of the current invention may include aspects of different marking systems described herein in combination on the same and/or on different animals.
  • sentinels 314d and 314d' include orientation markings 317a,a'.
  • sentinels 314d and 314d' may be distinguished based on characteristics of the chickens themselves and/or by tracking each individual over time.
  • sentinel 314e includes a markings 316e that include color coded (different colors are indicated by different hatching) lines.
  • the lines may be of different width and/or the width of lines may be significant in recognition.
  • the orientation and/or order of the lines may not be significant.
  • the orientation and/or order of the lines may be significant.
  • lines may be of similar colors but include different fill patterns (for example hatching, cross hatching).
  • colors may include visible colors (for example brown, yellow, blue) and/or colors in other wavelengths (for instance IR dyes and/or UV dyes), and/or a reflective substance and/or a fluorescent substance.
  • sentinel 314e may have an additional marking 317b that is used for tracking.
  • marking 317b may be a color that is easily spotted by the tracking sensor.
  • many sentinels may have the same marking 317b.
  • marking 317b may be used to facilitate tracking sentinel 314e when he is in a low resolution area. In the low resolution area, individual markings 316e may not be easily visible.
  • sentinel 314f includes a markings 316f that include color coded
  • lines may be of similar width and/or the width of lines may not be significant in recognition.
  • the orientation and/or order of the lines may be significant.
  • the orientation and/or order of the lines may not be significant.
  • lines may be of similar colors but include different fill patterns (for example hatching, cross hatching).
  • colors may include visible colors (for example brown, yellow, blue) and/or colors in other wavelengths (for instance IR dyes and/or UV dyes), and/or a reflective substance and/or a fluorescent substance.
  • individual animals may be recognized by the color combination of their respective markings.
  • sentinels 314g and 314h are marked with optical markings 316g,h, 317g,h that include a pattern of shapes.
  • the shapes may include squares and a triangle pointing at the chicken's head.
  • a shape may be color coded and/or include a fill pattern.
  • shapes may be of similar size and/or the size may not be significant in recognition.
  • the orientation and/or order of the shapes may be significant.
  • the orientation and/or order of the shapes may not be significant.
  • some or all of the markings (for example marking 317d,e) may serve as orientation markings.
  • 10 shapes (9 squares and a triangle) on sentinel 314h are each coded with binary color combination.
  • each combination may be used to identify one or more animals.
  • a marker may also optionally include a symbol, for example a letter or a number.
  • non-optical markings 318d,d',f,g,h there may be a non-optical markings 318d,d',f,g,h.
  • the non-optical markings may or may not be visible.
  • the non- optical markings may be color coded (for example 318g).
  • some and/or all of sentinels 314d-h may have an RFID sensor mounted to their head.
  • feeder 322c may include eight sections and each section may include a very short range RFID reader that registers the identity of sentinel 314d,e when he inserts his head into the feeder.
  • non-optical markings 318d,d',f,g can optionally be seen and optionally serve as orientation markings for the optical system.
  • an animal may be marked with more than one system.
  • two marking systems may optionally serve for separate purposes.
  • an RFID system may give accurate tracking of exactly how much time each sentinel spends eating (for example in some embodiments extreme crowding around a feeders and or slow frame rates may make the RFID system more accurate than the optical system for this task).
  • the RFID system can act as to verify identification made by tracking and/or distinctive optical marks.
  • non- optical markings may be used to re-identify an animal lost to tracking.
  • optical tracking may optionally be restarted. If a bird is lost to tracking and does not show up to a feeder for a long time, this may be a sign that the bird is dead or seriously incapacitated. In some embodiments, an animal may be tracked but its identity may be confused with another animal.
  • the marking system for example the RFID system and/or distinctive optical markings may be used to re-identify an animal.
  • an aspect of some embodiments of the current invention is to use an optical marking that are configured to reduce disruption to animal behavior.
  • the marker may be invisible and/or minimally visible to the animal marked.
  • a bird that is blind to the infrared (IR) spectrum may optionally be marked with an IR marking.
  • the optical sensors may include an IR sensor and or filters that are sensitive at different wavelengths allowing multiple distinctive "colors" in one or more spectrums (for example, IR, visible).
  • an animal may be marked with a visible color that does not arouse strong behavior aberrations. For example the applicant found that for chickens brown, green or blue may not induce pecking behavior as much as other colors (for example red).
  • markings may be color coded.
  • marking may include geometric patterns, for example differing width stripes like a barcode.
  • a sentinel may be marked with a marker that becomes visible under specific conditions.
  • a marking may be invisible and/or minimally visible under incident lighting.
  • an animal may be marked with a fluorescent marking that becomes visible under, for example strong ultra-violet (UV) radiation.
  • UV ultra-violet
  • a bird may be marked with a reflector that is obvious to a strategically placed light and detector from a particular direction but less obvious casual observation.
  • a bird may be marked with a selective dye that absorbs preferentially at a particular wavelength. The dye may, for example, be nearly invisible to the naked eye, but be distinguishable under specific lighting conditions and/or when using a color narrow band filter and/or sensor.
  • using specific markers and filters or very specific color sensitivity of the camera system may simplify the surveillance system.
  • optical markings may be used that are visible under night lighting.
  • night lighting may be supplied in the IR spectrum.
  • sentinels will be tracked at night using IR detectors.
  • an animal may have IR mark used at night when there is less traffic and tracking may be simpler and during the day the IR marker may be augmented by visual markings that allow for more positive identification under daytime conditions.
  • lighting can be run continuously or intermittently at night.
  • Markers may include for example a dye, a mounted device, a sticker, a fabric, a semi passive electro-magnetic device (for example an RFID), an active device (for example a light and/or a transmitter.
  • a semi passive electro-magnetic device for example an RFID
  • an active device for example a light and/or a transmitter.
  • a marker may be semi-active.
  • a fluorescent marker may not interfere with normal activities under incident lighting, but may glow and allow chicken identification when exposed to strong ultra-violet (UV) light. Reflective colors may increase visibility of an animal in poor lighting conditions.
  • a marker may include an active element.
  • LED lights may be mounted on a bird and/or a radio transmitter.
  • An LED may optionally have a distinctive color and/or a color combinations.
  • a LED may optionally flicker in time, for example transmitting any personal code.
  • An active beacon may be activated periodically and/or by remote control to allow re-identification of an animal that has been lost and/or location of a marker that has fallen and/or recognition and removal of a marker when necessary (for example when an animal is slaughtered).
  • a calculation can be performed based on a flickering marker to determine, for example distance and or speed.
  • An active marker may be activated by certain activities, for example resting over a certain period of time or at a certain hour, drinking, eating.
  • a marker may include a combination of the above mentioned elements.
  • a combination of colors may be combined with varying width of lines.
  • an orientation mark may be the same for all animals (for example a purple dot on the tail and/or head) in addition to a distinctive color combination on the back.
  • an orientation mark may serve on or more of many functions. For example, it may help locate an animal. Optionally, it may help prediction of direction of movement for example to assist tracking. Optionally, it may help orientation for reading a color combination. Optionally, it may help in recognizing certain activities. For example, from the direction of the marker it may be possible to determine if an animal is lying on its side and/or back, stretching its neck and/or preening its feathers, eating and/or just standing near a feeder, walking forward and/or jumping backward etc.
  • optical detectors serve for direct observation of signs of health and disease.
  • an IR camera may be used to measure heat emission from poultry, for example unusually high or low temperatures may be a sign of a disease.
  • visual range cameras may be used to detect blood stains in stools and/or on chickens and or on wall and/or on feeding bowls. Such stains may indicate presence of a disease or a problem of pecking within the house. Observations may optionally be made in multiple bands (for example using narrow bandwidth sensors and/or filters). Some symptoms and/or markers may be apparent in one band while others in another band.
  • a house observation system may be used by a human.
  • the system can provide a map of the coop on a mobile device (for example a mobile phone or notebook computer) showing the location of a sick chicken.
  • a laser pointer may be supplied to point out a sick chicken.
  • the person can point a laser pointed at a bird and the system will tell him when he find the chicken for which he is searching.
  • a calibration device may be supplied.
  • a coop bar can be placed with a number of grades of color and/or temperature (controlled for example the heating element and thermostats).
  • the bar may optionally be placed in coop to serve as a standard table and allows to calibrate visual and/or IR cameras for example under changing environmental conditions (for example dust and/or humidity and/or lighting).
  • the calibration can optionally be adjustable to allow course and/or fine calibration.
  • the bar may be made for example, from aluminum, stainless steel and metal material, polymer, ceramic, and/or painted and/or coated with a particular and so on.
  • Fig. 4 illustrates an exemplary embodiment 400 of a portion of a poultry house with a monitoring system and a trajectory 429 of a sentinel in accordance with some embodiments of the current invention.
  • the monitoring system includes an optical sensor 424 in communication with a processor 428.
  • a resolution enhancer In some areas of the chicken house (for example near feeders 422a,b) there may be a resolution enhancer.
  • the resolution enhancer 426 may include a light source (for example a higher power visual light to improve visual image quality and/or a UV light to activate fluorescent markings) and/or a high resolution camera (for example there may be a wide angle camera tracking animals in large area and a higher resolution camera that allows a more detailed look at interesting details.
  • a grid may be supplied (for example painted on the floor) to make it easy to direct the high resolution camera at a location identified in the wide angle image)) and/or a RFID sensor.
  • a special band optical sensor may be used.
  • a sensor may detect coded LED signals.
  • the sensors may be spread around an enclosure and read timed LED signals and/or a sensor may be located at a specific location with a trigger that activates an LED, for example when an animal passes by.
  • a wide angle sensor may be used.
  • the image quality may optionally be higher towards the center of the field of view and/or near the camera.
  • the monitoring system may for track states of a sentinel and/or its movements at and/or between various points 423a-n along the trajectory.
  • sensor 424 makes an image of the area at the end of a ten second time frame.
  • sentinel birds are located in the image and for each bird various parameters are computed. For example, it may be computed how far the bird moved since the previous time frame. From the distance moved, a rate of locomotion may be computed. When a bird lies in one place over a few frames the amount of time lying in place may optionally be recorded. Time spent near feeders and water sources may optionally be recorded etc.
  • a sentinel may be tracked, for example, starting at point 423a. After ten seconds, in the next time frame the sentinel has moved to point 423b. Point 423b is near a watering trough 420. For example, the sentinel may remain near the watering trough for between forty and fifty seconds. In the example, the sentinel will be found around point 423b in four consecutive time frame images.
  • the system may optionally record the location of the sentinel.
  • the system may optionally check the position of the sentinel's head and/or body and/or the position of other chickens near the watering trough to determine a state of the sentinel. For example, the sentinel may be drinking, and/or waiting for another chicken to move out of the way so that he can drink and/or fighting and/or preening and/or bathing etc.
  • the sentinel continues on trajectory 429 to points 423c,d,e, showing up at each point 423c,d,e in only one image.
  • the long distances between points show that the sentinel is walking fast.
  • the general direction of the sentinel is toward feeder 422a.
  • the speed of motion and/or the tortuosity of the path may optionally be recorded and/or interpreted.
  • the images while the sentinel is walking by point 423c-e may be examined to for signs of a locomotion problem (for example did the sentinel walk on a convoluted course because the direct path was blocked by other chickens and/or was the sentinel limping etc.
  • a tendency of an animal to walk torturous paths and/or change directions less often than normal and/or less often than other animals may be a sign that the animal is sick and/or becoming sick.
  • the sentinel comes to point 423f near feeder 422a.
  • the sentinel may remain near the feeder approximately in the same point 423f over five or six 10 second time frames.
  • the sentinel may be recorded in five or six images near point 423f.
  • the system may monitor, for example the sentinel's activities, whether he is facing the food and/or facing another chicken and/or eating and/or sitting and/or standing and/or locomotion and/or preening etc.
  • the system may keep track of a sentinel's personal habits.
  • the system may track which feeder a sentinel uses. For example, if a sentinel starts using a different feeder this may be a sign of some new condition (of the feeder and/or of the sentinel.
  • image enhancer 426 is located near feeder 422a.
  • image enhancer 426 may include an ultra-violet light source.
  • the sentinel may optionally be tagged with a fluorescent tag identifying the particular sentinel.
  • the resolution may be too poor to identify each individual chicken in most of the chicken house.
  • the system may, for example, try to track individuals also in the low resolution areas. When the individual comes to a high resolution area his identity may be verified and/or corrected (for example if a misidentification and/or confusion had occurred). If the individual identity is lost, he may be re-identified when he comes to a high resolution zone. For example, when the sentinel in the example of fig.
  • a high resolution zone may include, for example, a better light source, a higher resolution sensor, a RFID reader etc.
  • high resolution zones may be located where tracking is difficult (for example in crowded regions near feeders etc.)
  • a sensor may be a high resolution zone, but further away, the sensor may have a limited ability to distinguish markings, for example as illustrated in Fig. 10.
  • the sentinel may, for example wander towards a watering trough 420. On the way he may pass consecutive time frames at points 423g-i. Alternatively or additionally the sentinel may stop at some points (for example 423h for a few frames). While a sentinel remains in a single place over a few frames, the system may, for example, analyze various aspects of the images to determine the animal's status. For example, is he standing or lying down, are his eyes open or closed, which way is he facing, does he change positions, is he near other animals etc.
  • the system may track an animal's resting habits (for example does the animal only walk short distances and rest often and/or does he sometimes walk long distance before resting, does the animal move to comfortable areas to rest or does he rest even in crowded areas, does the animal tend to rest in warm spots and/or cold spots), whether the animal stays together with other animals in general, whether the animal is consistently associated with another a particular sentinel etc.
  • the system may also register aspect of the sentinel's appearance such as how he stands and/or sits (does he tend to lean to one side more than the other), does he tend to walk directly forward and/or slightly sideward. In some embodiments, some of these behaviors will not be clear in every image, but over time as a lot of images are processed a pattern and/or tendency may be discernible.
  • the sentinel may for example come to point 423j near water trough 420 and drink for two time frames and then move to point 423k to drink for another three time frames.
  • the system may record such details as whether an animal stays in one place while eating and/or drinking or moves.
  • the system may record for example, how much time the animal eats between acts of drinking and/or how long the animal waits after eating before drinking etc.). For example, statistics could be computed on how much time a chicken spends by feeders, how many times a chicken visits the feeders, how much time the chicken spends at the feeder each time he visits, what portion of the time that the chickens spends near the feeder is he actually eating.
  • Such behaviors may optionally be adjusted for example to environmental conditions for example the temperature (for example an animal may be more lethargic, spend more time near water on a hot day). Behaviors optionally may be compared to other sentinels in the virtual flock and/or to flock statistics. For example, if one sentinel doesn't drink it may be a sign that he is sick; if all the sentinels suddenly stop drinking it may be a sign that there is something wrong with the water system.
  • the sentinel may go to an edge of the chicken house, for example from points 4231,m to point 423n.
  • the chicken may, for example sleep for a long period at point 423n.
  • the system may optionally record movements while sleeping (for example rolling) and/or the consistency of sleeping (does the animal sleep for long periods straight and/or does he wake up and back to sleep often).
  • an individual sentinel may have individual marking.
  • each sentinel may be monitored individually.
  • Each sentinel having an individual mark may help when, for example, tracking of one or more sentinel fails, for example sight of the sentinel is lost. In some cases, sight may be lost of a number of sentinels.
  • Having individual marks on sentinels may help the system re-acquire identities of sentinels and/or associated sentinels with their medical history information. For example, when a sentinel has been lost, an image may be scanned and/or a sensor may scan an area to locate the mark associated the lost sentinel.
  • the frame rate may vary as needed for monitoring the condition of the flock. For example, when rapid movement occurs the system can collect frames at high speed, when there is little movement, the system can collect the frames at a slower rate.
  • the group of sentinels may include a virtual flock.
  • the virtual flock may be representative of the entire population.
  • the virtual flock may contain, for example, between 200-1000 individuals. In some embodiments the number may be large or smaller.
  • each sentinel may be marked with an individual marking, but each mark may be repeated. Individual sentinels may optionally be monitored.
  • Tracking may optionally be used to preserve the identity of individual sentinels. When a confusion occurs on the identity of some of the sentinels it may optionally be possible to clarify the identities by the markings. In some embodiments, a portion of the sentinels may be lost. In some cases, for example a small population, every animal in the population may be tracked.
  • sentinels may include birds having a different natural coloring than the rest of the flock.
  • a species may be bread to have a coloring that makes it possible to recognize particular individuals.
  • a breed of chicken may include a tendency for a portion of the birds to have a distinct coloring on a small part of their body.
  • animals may be bred to allow marking.
  • birds may be bred to not to peck at markers etc.
  • a chicken may be bred wherein between 90 and 99% of the chickens are white and between 1 and 10% of the chickens have an obvious marking somewhere on their body.
  • a single mark may be used for all of the sentinels and/or a few marks may be used, each mark being used on a large subflock of sentinels. For example there may be 1 to 20 subflocks.
  • the sentinels may optionally be tracked. Statistics may be kept for the entire virtual flock and/or for each subflock. For example between 2000 to 4000 sentinels may be marked in a population of, for example, between 30,000 to 60,000 animals. Optionally, some individual sentinels will be tracked. In some embodiments, the system may track a condition of some individual sentinels by an idiosyncratic parameter, for example, distance walking, eating, drinking.
  • the system may optionally have a minimum frame rate to preserve tracking and/or identity of sentinels.
  • the minimum frame rate may be between a frame per second and a frame every twenty second. The minimum frame rate may continue to preserve tracking even when data is not needed to health monitoring.
  • individual markings may have fine aspects (for example different width stripes) that allow identification of a particular individual and more obvious aspects (like the color of the stripes) that allow for identification of a subgroup and/or separation of two birds even when the picture resolution is low.
  • different regions may be monitored separately.
  • a chicken house may be divided into four regions.
  • Each region may have a separate marking scheme.
  • each region may include chickens numbered from one to one hundred.
  • Statistics may be compared between regions. Changes in one region with respect to another may, for example, be a signal of a problem.
  • detailed tracking of animals may take place in a various sites.
  • all or nearly all of the animals in those sites may be monitored.
  • Each site may have a relatively small area of, for example, between 1 to 10 square meters.
  • the sentinels in this case may optionally be a dynamic sample of the population. The size of the sample may remain more or less fixed while the individuals in the sample may change over time.
  • methodology of detailed tracking of unmarked birds in a few locations may be used in combination with tracking marked sentinels.
  • lost sentinels may be identified.
  • the population may be tracked statistically.
  • one or a few cameras may monitor all or part of a chicken house (for example between 70 to 100% of the chicken house) and track all or part of the population (for example between 70 to 100% of the population).
  • each part of the house may have one or more dedicated cameras.
  • various parameters may be tracked for a sample of and/or the entire population. For example, the distribution of speeds of movement and the distribution of states (for example standing, sitting, lying, walking, Running, flying, eating, drinking, preening, sleeping) may be monitored. The system may also for example track when an animal "migrates" from one area of an enclosure to another.
  • various parameters may be correlated in time and/or according to individual animals. For example, what portion of animals that are near the feeders are eating, lying, standing, preening. For example, what portion of the animals that are lying down are also sleeping.
  • different parts of a single poultry house may be compared and/or different poultry houses may be compared.
  • Comparisons may be made historically to populations in the past and/or within a single population over time.
  • the development of the population may optionally be tracked. Changes in behavior statistics over time and/or space may be tracked. Changes over time may be compared to previous poultry houses or contemporary poultry houses. A change in behavior from a previous day may, for example, indicate a malfunction of a heater and/or ventilator and/or water system and/or an external factor, and/or a problem with feed and/or a disease and/or the presence of an intruder.
  • an image may be made in each time frame of 10 seconds and/or for example between 2 to 10 seconds and/or every half a minute and/or once a minute. During the time between images, previous images may be analyzed. Statistics may be computed of activities on a for example an hourly basis and/or daily and/or at other intervals. In some embodiments images may be made in groups, for example images may be made once every ten seconds for 20 minutes and them once every second for 30 seconds and then back to one every second. For example the high rate images may be used to reveal detailed movements of sentinels while the low rate images are used for tracking and static details. The frame rate may change. For example a high frame rate may be used during the day and/or in crowded area of the chicken house.
  • Optical monitoring may be integrated with other methods.
  • accelerometers may be placed on some or all of the sentinels and/or non-sentinel animals and/or food and water consumption may be monitored and/or levels of gases in the air of a poultry house and/or temperature, of one or more animals and/or the environmental temperature etc. may be monitored.
  • one may monitor the time a chicken stands near feeders and the weight gain, for instance this may help recognized and/or differentiate loss of appetite and/or malabsorption of food. This may help recognize for example intestinal parasites and/or chronic conditions, and/or animals that cannot get to food due to social factors (other animals prevent him from reaching the food), such a comparison could also be made for groups of animals.
  • Various optical observations may be integrated.
  • an IR camera may be used to track movements of an animal and also measure the heat emissions of the animal. For example, decreased quantity of movement with increased and/or decreased body temperature may be a sign of an infection.
  • Visual and IR data and/or images may be integrated.
  • Various activities may be measured to indicate the status of a sentinel and/or the group of sentinels and/or the population of animals.
  • statistics may be computed, for example average, standard deviation, maximum, minimum etc.
  • the system may optionally be able to track various parameters such as the cumulative amount of time involved in the activity; the length of each session of the activity, the number of sessions and/or the length of breaks between sessions of the activity.
  • there may be particular parameters.
  • locomotion time, speed and/or tortuosity of path may be tracked.
  • activities may be subdivided, for example locomotion may be divided into for example walking, running, flying etc.
  • comparisons may be made, for example between animals, to the group as a whole and/or a subgroup, over time, at different times (for example morning, afternoon, night), according to location (for example near water, near food, in crowded zones, in non- crowded zones, in a particular area, eating at a particular feeder) between groups and/or subgroups, to standard values for normal and/or abnormal behaviors.
  • location for example near water, near food, in crowded zones, in non- crowded zones, in a particular area, eating at a particular feeder
  • locomotion for example walking, running, flying
  • abnormal behaviors for example ticks, spasms, odd walking, walking along a crooked path.
  • the system may track an individual and/or keep statistics of a group of animals.
  • the system may track statistics describing the behavior, for example an average and/or a standard deviation over time and/or over a group of animals.
  • the system may track for example the portion of time an animal spends in that behavior (for example over an hour period how much time did an animal spend walking) and/or a magnitude of the behavior (for example speed walking, distance walked) and/or the length of the session of the behavior (for example how long does the animal walk before taking a break) and/or the length of breaks between sessions of the behavior (for example how long are the breaks between periods of walking) and/or the number of times that the animal performs the activity and/or a ratio of a measure to another activity (for example the ratio of the time the animal spends walking to the time the animal spends sleeping).
  • a magnitude of the behavior for example speed walking, distance walked
  • the length of the session of the behavior for example how long does the animal walk before taking a break
  • the length of breaks between sessions of the behavior for example how long are the breaks between periods of walking
  • a ratio of a measure to another activity for example the ratio of the time the animal spends walking to the time the animal spends sleeping.
  • a threshold to a measure for example an act of walking is only counted if the animals walks at least two meters and/or for at least ten seconds etc.
  • Activities may be classified and/or counted according to where they take place (for example standing near a feeder may be counted separately from standing in an empty area).
  • Behaviors that may be measured include for example walking, flying, eating, drinking, sleeping, sitting, lying, running, preening, standing, being in a particular location.
  • the system may store images and/or statistics of behaviors and/or other data. Some data may be stored erased quickly (for example raw image data may be retained between 10 seconds and and/or raw behavior statistics may be retained between an hour and ten days and/or processed statistics may be retained permanently and/or erased after a group is slaughtered.
  • the system may optionally track certain symptoms of disease and/or health status directly.
  • the system may characterize certain states and/or movements, for example walking, cleaning feathers, running, eating, drinking, lounging, open eyes, fully or partially closed eyes.
  • the system may optionally classify some actions as normal and/or abnormal.
  • certain appearances may be detected and classified for example as normal and/or abnormal and/or pathological.
  • chickens standing still with bristling feathers and/or eyes half-closed or closed and/or birds standing with head tucked down and/or birds have difficulty breathing (for example an open mouth and/or rising and falling tail) and/or movements of breath and tail visible and/or birds walking and limping and/or twitching and/or fluttering.
  • the system may optionally recognize normal and/or abnormal grouping and/or huddling behaviors.
  • the system may optionally recognize normal and/or abnormal and/or pathological colors. For example, the system may recognize when a white chicken becomes dirty brown from diarrhea and/or the system may recognize blood stains blood around the anal area.
  • the system may include cameras in different wavelengths covering the same and/or different zones. For example some markings may be apparent in some wavelength and not in others.
  • IR sensors may be used to detect heat emission from animals.
  • heat emission data may be a useful in tracking the prevalence and acuteness of avian influenza. For example, if high IR radiation levels are detected throughout a chicken house, the system may warn of potential heat stress and/or heat stroke. If the IR signal is unusually weak, the system may optionally issue a warning for cold stress. Based on the IR measurements and/or behavior of the flock, the system may automatically adjust the environmental conditions of an enclosure.
  • the ventilation system may be turned up to cool a chicken house. For example, if it is seen that the animals are too cold and/or are huddling together a heater may be turned up.
  • the system may track general movement data of the population and/or a virtual flock of sentinels.
  • the system may use general data to assess the health of the virtual flock and/or population without indentifying and/or tracking individual sentinels.
  • general processes that may be tracked include for example statistics on various processes such as average, standard deviation, maximum minimum, cumulative time, length of uninterrupted actions, and/or portion of the population involved in an action at a particular time etc.
  • General parameters that may be tracked include for example: locomotion (locomotion may be subdivided into different types for example walking, flying, running); population density in different areas for example around feeders, water troughs, sitting areas; resting; sitting, standing; preening; eating; drinking; fighting etc.
  • a user may be able to access historical and or real time data about the population density in any part of an enclosure (for instance a chicken house) and/or preference of the animals (for example food intake).
  • a user may be able to access data from the system, for example the portion of animals displaying a certain behavior, in real time or near real time. Access to the system may be via a dedicated user interface and/or a wireless system and/or over the Internet. For example a farmer standing in the chicken house may be able to communicate with the system and/or get data using a cellular telephone.
  • the current invention may track the progress of various stages of a disease outbreak. For example, the system may discern individual history of animals getting sick and the progress of the disease in the population. It may for example, be possible to develop interventions that prevent development of an epidemic by prevent a certain stage of the process and/or a way to recognize an outbreak at an earlier stage.
  • the current invention may be applied to interpret clinical trials of disease interventions.
  • the system of the current invention may optionally track details of a disease outbreak and/or the effects of an intervention. For example, key sub processes of an outbreak may be identified. Precise effects of an intervention may optionally be tracked.
  • the system may be used to identify animals developing signs of illness and take them for further testing.
  • a user may be able to access the current number of sick birds, and/or the number of sick birds at a certain time in the past and/or statistics about the number of sick birds over a period of time and/or the number of chickens newly infected over a certain time period and/or the number of birds whose health improved and/or the severity of the condition of birds (for example the severity of clinical symptoms and/or quantitative measurements of the aberrations in behavior).
  • the data may be used to track the condition of individuals and/or part or all of the population.
  • the current invention may be useful in identifying a susceptible portion of a population for clinical trials.
  • the current invention may track the effects of an intervention on a disease precursor and/or the effect that the intervention against the precursor has on the health of the population.
  • markings will include a tag connected to an animal.
  • the tag may include a RFID, a visually identifiable tag (for example color coded and/or bar code) and/or an active beacon (for example a remote controlled light).
  • a tag may be attached to an animal by a strap.
  • the strap may be configured to expand over time as an animal grows.
  • Figs. 5A,B illustrate an exemplary embodiment 500 of a strap that grows over time in accordance with some embodiments of the current invention.
  • embodiment 500 includes two elastic belts, a long belt 526 and a short belt 524. Each end of belt 524 is optionally attached by a respective ring 527, 527' to a corresponding end of belt 526.
  • Belts 524, 526 are optionally contained in a soft sleeve 528.
  • Sleeve 528 may for example, protect the skin on an animal from abrasion.
  • a strap may include single elastic belt that changes length.
  • the belt may be of a stretchable, for example elastic, for example the belt may be made of lycra and/or latex and/or rubber.
  • the dual belted strap of embodiment 500 is attached around a young animal. Rings 527 and 527' may optionally serve to hold the strap onto a marker for example as shown in Fig. 6D. While the animal is small, the strap may hold tight to the animal due to short belt 524. As the animal grows short belt 524 breaks (for example due to stretching) and/or decays at a planned rate and/or is actively released. The strap remains on the larger animal, being held for example by belt 526.
  • a strap may optionally include more than two belts of different sizes.
  • Figs. 6A-C illustrate exemplary embodiments of marker for mounting on a chicken in accordance with some embodiments of the current invention.
  • Fig. 6A illustrates an overhead view of a marker platform 621a having remote control releasable belts 624 and 626 for connecting to a chicken.
  • the exemplary embodiment of Fig. 6A includes eight remotely releasable rings 627a and two long belts 626 and two short belts 624. Each belt 624, 626 is connected to the marker by a pair of remotely releasable rings 627a.
  • one set of belts 624, 626 is wrapped around his right wing and the other set of belts 624, 626 is wrapped around his left wing.
  • the marker may optionally include a beacon.
  • the beacon may light up when it is released to make it easier to find and recover the marker after it falls.
  • the beacon may optionally be lit when a sentinel has been lost to make it easier to re-identify the sentinel.
  • the beacon may optionally be used by a caretaker and/or a veterinarian to locate the sentinel.
  • the beacon may optionally light automatically upon release from the chicken.
  • the beacon may optionally be controlled remotely, for example by a radio signal and/or by an optical signal.
  • Fig. 6B illustrates a side view of an exemplary marker platform 621b including an active beacon 616 in accordance with some embodiments of the current invention.
  • beacon 616 is raised by post 619 above a mounting platform 621b. Raising beacon 616 may optionally improve visibility of the beacon, for example when the chicken is in a crowd and/or fluffs his feathers.
  • beacon 616 may be raised between 0.5 to 2.0 cm.
  • active beacon 616 may include a light emitting diode (LED). Active beacon may radiate in the IR, Visible, microwave and/or UV spectrums.
  • LED light emitting diode
  • beacon 616 may light automatically from time to time. Alternatively or additionally, beacon 616 may light on demand, for example by remote control. Alternatively or additionally, beacon 616 may light under certain conditions (for example if there is some sign of distress of the host chicken and/or upon falling from the host chicken). In some embodiments beacon 616 may have recognizable color (wavelength). In some embodiments beacon 616 may send out a recognizable pattern, for example a pattern of flashes that identify the host chicken to the observation system.
  • platform 621b may include a strap 624 for attaching to a chicken.
  • Fig. 6C illustrates a composite embodiment 600c of an example of a marker platform 621c having various exemplary embodiments of releasable mounting pins 627c, 627c', 627c", 627c'” in accordance with some embodiments of the current invention.
  • various components of embodiment 600c may be used separately or in combination with other embodiments of a marker platform.
  • marker platform may be mounted to the back a chicken using two straps (for example embodiment 500 and/or strap 624) attached under respective wings of the chicken.
  • the straps may be connected to retractable pins 627c, 627c', 627c" and/or 627c'".
  • rings 527 and 527' of embodiment 500 may be hooked to retractable pins 627c" and 627c'".
  • a simple strap for example strap 624 may be hooked onto pins (for example, pins 627c and 627c').
  • a marker platform may include a radio receiver 630.
  • a processor 631 may close a switch 633 to connect a release mechanism to a battery 632 activating the release mechanism.
  • a release mechanism may be driven by a motor 639.
  • motor 639 may drive a pulley 641 that spins one or more threaded 634 pins 627c, 627c'" causing them to retract and release the strap.
  • the release mechanism may include an electromagnet 637 that retracts a pin 627c".
  • the release mechanism may include a heat sensitive self reforming pin 627c' (for example the pin may be made of nitinol).
  • to retract pine 627c' power is sent to a heating element 635 which may heat pin 627c' to a reforming temperature causing pin 627" to retract and release strap 624. 17.
  • markings may undergo changes and/or fading and/or corruption (for example a mark may disappear when a bird molts and/or sheds, holes may form in a mark and/or a geometry of a mark may change as an animal grows).
  • an automated system may mark birds.
  • the painter may use the sensors of the monitoring system and/or a dedicated sensor that detects when an animal is under a color nozzle and sprays a stain on the animal as it passes (the sensor may include for example, a proximity sensor, a camera, eyes sensitive to light, beam of light and/or a sensor that detects whenever an animal crosses the beam).
  • the sensors may include a mechanical sensor.
  • marked animal may be re-marked.
  • a manual and/or automatic system may be supplied to refresh an old mark.
  • a new mark may be placed on a previously marked animal and the system may be updated to recognize the new mark and associate it with the correct animal.
  • birds may be marked without regard to previous markings. Marking birds may optionally be manual and/or automatic.
  • Fig. 7 illustrates an exemplary method for marking sets of animals in accordance with some embodiments of the current invention.
  • an initial set of sentinel animals may be marked 736.
  • marking 736, 740, 744 may be automated (for example by a machine that may paint the animals that pass a certain location) and/or marking 736, 740, 744 may be manual.
  • the system will track 738 the first set of sentinels, for example in order to monitor the health of the population.
  • a second set of sentinels may optionally be marked 740.
  • the system will track 742 both the first set and the second set of sentinels.
  • the first set may be tracked 742 to monitor the health of the population and the second set may be tracked 742 to build up historical data in personal and/or group data files.
  • both the first and second group may be tracked in or to monitor the health of the population.
  • a third set may be marked 744.
  • the second and third set will be tracked 746 together to monitor health and/or build up a historical database.
  • time goes new groups may be marked and tracked as old groups become unrecognizable, for example until the animals are send to slaughter 748.
  • more than two sets of sentinels may overlap and/or there may be no transition period and only one set of sentinels may be tracked at a given time.
  • New sets of sentinels may be marked periodically. For example every three to thirty days new set of marks may be made. The new marks may be placed on previously marked animals and/or on new animals. During an optional transition period the system may monitor multiple sets of sentinels and after the transition period the system may stop monitoring one or more of the old sets of sentinels.
  • the system may recognize that an animal is dead for example due to lack of breathing movements and/or due to lack of locomotion over a long period (for example between one and three hours).
  • a user may inform the system of the death of an animal.
  • the user may take a picture of the animal or an identity tag (for example using a cell phone) and send the picture to the system (for example via the Internet); alternately or additionally a user may have a sign the he leaves in place of a dead animal such that when the system detects the sign it marks that animal that had been in that location as dead (the sign may optionally be moved once the system has detected it); alternatively or additionally the user may hold up a dead animal in front of a camera for a prescribed period of time as a sign that it died; alternatively or additionally, there may be a location for placement of dead animals and the system may periodically check the location.
  • Fig. 8 is a flow chart illustration of an exemplary embodiment 800 of a method to adjust 853 optical tracking of livestock in response to losing 852 track of one or more animals in accordance with some embodiments of the current invention.
  • the method optionally includes one or more of four general strategies: searching 854 for the lost animal, giving an estimated accounting 856 for the lost animal, continuing tracking 860 the rest of the animals with optional compensations for the changes in the number and/or content of the sample, replacing 858 the lost animal with a new animal.
  • the system may adjust tracking to avoid further loses. For example, the system may increase the frame rate. For example the system may send a message to a user that better tracking is needed (for example more cameras and/or better lighting and/or more computing power to increase the frame rate.
  • searching 854 may be focused in a selected 862 location and/or time.
  • the search may be focused in a vicinity where the animal was lost and/or in a predicted direction of movement and/or in a vicinity where the animal is accustomed to go and/or in a vicinity where animals generally pass by and/or in an area of enhanced sensing resolution and/or the search may be made when there are free resources (for example at night when animals may be moving less and tracking optionally require less resources) and or at night when there is less background light and/or movement and it may be easier to spot the lost animal.
  • searching 854 may be over the whole domain of the population and/or constantly over time.
  • searching 854 for a lost animal may include optical scanning 859 to locate the lost animal.
  • Optical scanning may optionally include dedicating 861 resources of an optical sensor system to finding the lost animal.
  • a sensor 855 used for tracking animals may be used for part of its time to scan for the lost animal.
  • processing 869 resources may be dedicated 861 to searching for the lost animal in existing images.
  • the search may optionally include improved tracking in images from the time that the animal was lost to try to retrace the tracking of the lost animal.
  • the search may optionally include analyzing past images and/or data on the lost animal to ascertain an identifying characteristic with which to recognize the missing animal (for example the animal may have customary locations where he may be found and/or may have an easily spotted behavior and/or mark).
  • the search may optionally include analyzing a current image to recognize the lost animal. Alternatively or additionally both sensing and processing resources may be dedicated to searching for the lost animal.
  • searching may include use of non-optical 864 recognition means.
  • animals may have been mounted with a non-optical location means.
  • an animal may be mounted with a RFID that allows identification of the animal when he comes near an RFID reader.
  • the animal may be mounted with a radio locator and/or a GPS detector and a data transmitter that may report the location of the animal.
  • non-optical 864 recognition means may be activated automatically periodically and/or be activated remotely (for example by broadcasting an activation message) and/or may be activated by some secondary occurrence (for example when the animals approaches an RFID reader located by a feeder) and/or may be activated by an intervention (for example herding animals through a gate containing an RFID reader).
  • enhanced 863 optical means may be used to search 854 for the lost animal.
  • the enhanced 863 optical means may include for example a light source.
  • a UV 876 light source may be used, for example, to cause a fluorescent marker to glow and/or a IR 872 radiation source and or sensor may be used, for example, to bring out a IR marking (that may be seen for example with a IR sensor).
  • a reduced lighting condition may be used, for example, to make a glowing fluorescent marker easier to spot.
  • a narrow band 882 sensor and/or light source may be used, for example to make the lost animal easier to spot with respect to other marked animals.
  • a high resolution sensor 880 may be employed and/or a high intensity light source (for example increasing the lighting intensity over the background intensity of the animal pen).
  • a high intensity light source for example increasing the lighting intensity over the background intensity of the animal pen.
  • an active beacon 878 may be used.
  • a LED beacon may be mounted on the animal.
  • the beacon 878 may be activated remotely and/or automatically from time to time or due to some occurrence, for example when the animal enters a certain area.
  • searching may employ both optical and non-optical means.
  • a lost animal may be replaced.
  • a new animal may be taken into the sample.
  • the new animal may be fresh and unknown and/or the system may have reserve animals that it tracks and incorporates in the sample when needed.
  • the new animal may be chosen to have characteristics (for example sex, age, genetic characteristics, weight, and/or history etc.) similar to the lost animal.
  • a lost animal may continue to be accounted 856 in the sample.
  • the animal may be accounted 856 for a limited time or for an unlimited time.
  • the system may extrapolate from the animal's previous condition and/or behavior to predict a current condition and/or behavior.
  • the predicted condition may optionally be averaged into the sample.
  • the predicted data from the lost animal may be weighted 866 differently from real data from other animals. For example, in the first day after the animal is lost the predicted data may have half the weight of real data from other animals and on the second day a quarter of the weight etc.
  • the system may assume that the lost animal is not turning up is because it is dead and/or sick 874.
  • the lost animal has an RFID which should be read when he goes to eat, his not showing up may be a sign of sickness or death.
  • the fact that a lost animal is not detected may be assumed to mean that he is normal and healthy 875 (otherwise he might draw attention to himself).
  • the system will continue tracking the remaining sample of animals.
  • the continued tracking may optionally include compensating 860 for the missing animal.
  • the system may put an extra weight on data from animals with similar characteristics to the missing animal for example to make the sample of animals more closely representative of a larger population. For example, if the missing animal was a female, the system may put an additional weight on female animals to balance the missing animal.
  • Fig. 9 is a flowchart illustration of an exemplary embodiment 900 of a method of adjusting 953 tracking of a sample of animals when the identities of some of the animals become confused in accordance with some embodiments of the current invention.
  • the terms confused and unidentified are used herein both for animals whose identities are totally undifferentiated and animals for whom there is some basis to differentiate their identities but there remains a significant confusion about their identities, for
  • adjusting may include one or more of: re-identifying 954 the unidentified animals, replacing 958 the unidentified animals, continued tracking 956 of the unidentified animals (optionally making allowance for the in-exact identification) and/or tracking 960 the remaining animals (optionally tracking the remaining animals with optional compensations for the changes in the number and/or content of the sample.
  • tracking breaks down and/or when animals cannot easily be differentiated For example this may occur when animals are not marked with individually distinguishable markings (for example when two animals have the same marking). For example, this may occur even animals are marked with individual markings, but the markings are not clearly discernible. For example there may be a location where the resolution and/or the lighting are not good enough to discern individual markings. For example, the markings of the unidentified individuals may have become difficult to distinguish due to dirt, wear, molting (for example of hair or feathers on which a mark is painted).
  • the system may attempt to re-identify 954 the unidentified animals.
  • Re-identification 954 may optionally be in a selected 862 time and/or location, for example similar to searching 854 for a lost animal.
  • Re-identifying 954 an animal may include optical 959 and/or non-optical 864 means and/or a combination thereof.
  • unidentified animals may be replaced 858 with new animals.
  • Replacing 858 animals may be used, for example, when the markings on one or more animals become difficult to recognize.
  • there may be a transition 957 phase. During the transition phase, the unidentified individuals may continue to be tracked.
  • tracking may continue 956 for the unidentified individuals.
  • old observations 965 of each unidentified individual before their identities became confused and new observations 967 are ascribed 972 to each individual with a weight depending on the degree of confusion of the animal's identity.
  • the criterion to judge the behavior of the individual may optionally be adjusted with regards to old observations 967, new observation 965 and/or weights 966 optionally depending on the degree of confusion in the identification of the individuals.
  • New observations 967 may optionally be compared 984 to old observations 967 may be compared to clarify 986 the animals' identities.
  • the data for an unidentified animal may be stored under a temporary folder and/or under a temporary identification as long as there is significant doubt about the animal's identity. Upon identifying the animal, the temporary data may be integrated into the animal's permanent record.
  • first animal-A becomes confused 952 with a second animal-B.
  • animal-A was an unusually active animal with an activity score of 80 and animal-B was unusually passive animal with an activity score of 30.
  • a first ambiguous animal-0 is really animal-A and a second ambiguous animal-0' is really animal-B.
  • an animal whose activity level is reduced points in the activity scale from a previous level is considered sick.
  • each ambiguous animal will be assigned a historical activity value equal to the weighted 966 average of the previous values of animals-A,B.
  • the reduction criteria for an identified animal 10 points
  • the correlation of the newly measured activity values with the old values corroborates the identity of animal-0 with animal-A and animal-0' with animal-B.
  • the certainty of the identification may then be increased, for example in the next step the certainty levels will be clarified 986 to 75% certainty that animal-0 is really animal-A and animal-0' is really animal-B.
  • the ascribed 972 activity values will include a weighted average of the new observation 965 and the ascribed 972 old observation 967.
  • Fig. 10 illustrates a schematic view of a sensor 1024 in a chicken house in accordance with some embodiments of the current invention.
  • Sensor 1024 may include, for example, a digital camera with a fisheye lens (for example the lens may be a wide angle lens of between 6 and 20 mm and/or the field of view may be between 120° and 170°).
  • the fisheye lens may allow relatively clear viewing of chickens directly under the lens, for example in zone A.
  • sensor 1024 may for example facilitate distinguishing between markings on animals and identifying individual animals in zone A.
  • zones B on the periphery resolution may be poorer and/or there may be significant distortion.
  • sensor 1024 may for example facilitate tracking an individual but low resolution and/or distortion may make it difficult to positively identify the animal based on markings.
  • zone B Sometimes an animal in zone B may be positively identified (for example he has been tracked since leaving zone A).
  • Fig. 11 illustrates an exemplary method of continuing tracking after confusion of the identities of two or more sentinels in accordance with some embodiments of the current invention.
  • the identity a sentinel may become confused 952 (for example the fine differences between markings of individual sentinels may not be distinguishable, but the presence of markings delimitating an animal as a sentinel may still be recognizable for example due to one or more of being in a low resolution zone, being blocked from the camera, poor lighting and/or dust).
  • the system may optionally assign 1156 the sentinel a temporary identity and track him.
  • the system will then take the stored data and integrate 1172 it with the sentinel's original file. In some cases it will not be possible to identify 1186 a sentinel from his own markings, but it will be possible to identify 1186 him using a process of elimination.
  • Fig. 12 illustrates an exemplary embodiment of an automatic chicken marking device in accordance with some embodiments of the current invention.
  • a chicken reaches a predetermined position in a box 1288 he may optionally be detected by a sensor 1255.
  • a marker 1216 is sprayed onto the chicken by an automated sprayer 1289.
  • Sprayer 1289 may include for example pressurized tanks of paint and/or computer controlled valves and/or sprayer 1289 may work for example like an inject cartridge of a printer.
  • marker 1216 may include a coded individual marking and/or an orientation mark and/or a tracking mark.
  • mark 1216 may be sprayed on an animal's head, back, tail or other body part.
  • sensor 1255 may indicate the identity of a chicken (for example in some embodiments a chicken may have an RFID on its head and sensor 1255 may include an RFID reader).
  • the marking device may be used to recognize a sentinel and remark him with a specific pattern when his old marking fades. Alternatively or additionally, may not recognize the identity of a chicken.
  • the identity of the chicken may be supplied by an optical sensor that saw the chicken when he entered box 1288. Alternatively or additionally, the marking device may be used to point a mark an unidentified chicken.
  • FIG. 13 is a flowchart illustrating an exemplary embodiment of a method for analyzing a condition of an individual sentinel and/or the group of sentinels and/or the population of animals in accordance with some embodiments of the current invention.
  • the background of the analysis may optionally include assessing 1391 the status of the group.
  • Data may be collected 1392 on behavior and/or appearance of individual sentinels. Alternatively or additional data may be collected on environmental conditions and/or on group behaviors.
  • the collected data may be processed 1393 for example to normalize for confounding environmental conditions and/or by computing statistical summaries etc.
  • the data may optionally be integrated 1394 to analyze the status of the virtual flock of sentinels.
  • the status of each individual may then optionally be compared 1395 to the virtual flock.
  • Comparison 1395 may be useful for example to differentiate individual changes in status (for example getting sick, recovering, breeding etc.) from changes that are occurring on other levels (for example environmental changes, changes occurring due to growth [For example chickens are raised in large groups of the same age birds. The birds grow and change very quickly, comparison of the individual to the group may help differentiate changes due to growth and changes due to disease or other factors]).
  • Comparison may optionally include comparing an individual to group statistics for example mean and standard deviation. Comparison may optionally include computing a rank with respect to a certain behavior [for example the 14 th most active, the 150 largest drinker etc.).
  • the system may optionally look for and/or analyze 1396 changes in the relationship between the individual and the virtual flock.
  • an animal's condition is deteriorating 1397 and/or when the condition is significant 1398 to the entire virtual flock and/or when there is a significant change 1399 in the status of the virtual flock, a user may be notified 1377.
  • the system may update and/or fix sentinel identities 1386 and return to assessing 1391 the group status.
  • Figs. 14 and 15 show an exemplary healthy bird trajectory 1429 and an exemplary sick bird trajectory 1529 respectively each measured from images made every ten seconds over a twenty minute period in accordance with some embodiments of the current invention.
  • a healthy bird may, for example, walk faster and/or further than a sick bird.
  • a healthy bird may, for example, walk more and/or rest less than a sick bird.
  • a healthy bird may, for example, spend more time eating and/or walking and/or drinking than a sick bird.
  • a healthy bird may, for example, walk for longer periods and/or rest less often than a sick bird.
  • each spot where the chicken was detected in one image is marked "t".
  • the spot is marked in the figure as tx3.
  • Locations where the animal ate are marked t f and locations where she rested t r and locations where she drank t d .
  • An exemplary feeder 1422 and exemplary watering trough 1420 are depicted.
  • the healthy chicken drinks more.
  • the ratio of time spent in various behaviors may be computed.
  • Figures 16A,B are a schematic illustrations of an exemplary embodiment of a small behavior change that may be a precursor to an epidemic in accordance with some embodiments of the current invention.
  • the low level infection may, in some cases, not produce clinical symptoms of the disease and/or minor symptoms, but it may, in some cases, cause measurable behavior changes using the vitality meter, for example, acceleration and/or an optical observation system.
  • reoccurring low order infections may produce waves of behavior aberrations.
  • the waves may, in some cases, grow with time.
  • the behavior changes may grow continuously. Growth may be an increase in the number of animals affected and/or an increase in the time for recovery and/or an increase in the intensity of the behavior changes and/or aberrations and/or increasing frequency of occurrence.
  • Figure 16A schematically represents the number of animals in a section of a poultry house showing unusual nocturnal activity.
  • Unusual nocturnal activity may include increased movement, increased rolling, decreased rolling, decreased time sleeping, increase nocturnal bowel movements, increased nocturnal visits to water and/or other activities.
  • a group of animals may be affected by a low level infection and or an external parasite and/or an environmental disruption (for example too much light and/or noise at night). The condition may not have obvious clinical symptoms, but it may disturb the animal's sleep.
  • Such infections may be important to catch early for example because they may reduce productivity of the animals and/or weight gain and/or the parasites might spread a more significant disease and/or lead to social breakdown for example pecking and/or fighting and/or reduce the resistance of the animals to a more serious infection.
  • Sleep disturbances may also be a result of other conditions for example, it may be an early sign of an outbreak of a respiratory infection and/or the parasites may be a secondary effect of some other disease for example causing the animals to clean themselves less.
  • other signs of illness and/or disease that may be monitored include deaths, reduction in weight gain, reduction in efficiency of food conversion, changes in appearance (for example, skin infections, fluffed un-groomed and/or dirty feathers), an increasing in grooming, a decrease in grooming, an increase in pecking, and increase in fighting, huddling of animals together, reduction in activity, reduction in specific activity, increase in resting and/or sleeping, and/or decrease in resting or sleeping.
  • baseline nocturnal behavior is shown for the first 9 days.
  • a few animals are affected by a parasite.
  • they may not show clinical signs of illness but may be disturbed at night causing increased nocturnal activity.
  • the increased nocturnal activity 1624a may optionally not be statistically significant in and of itself and may optionally not arouse any alerts.
  • the first group of animals recovers by the thirteenth day.
  • a second group is affected. Since the pathogen may have spread since the first infection, the second infection may be more serious (more animals may have been exposed and their exposure levels may be higher). This results in a second wave of high nocturnal activity 1624b.
  • the second wave may have a longer length (continue for more days) and a larger amplitude (the peak nocturnal activity is higher) than the first wave.
  • the increasing wave of behavior aberration may trigger sending an alert to an animal manager.
  • the first alert may for example have a low level of certainty.
  • the second group of animals may, for example, recover by the eighteenth day. Starting on the nineteenth day another, larger group may start having increasing nocturnal activity 1624c. In the example, the higher significance of the third event (nocturnal increase in activity 1624c) and/or the obvious growing wave pattern may trigger a high certainty alert of a coming epidemic.
  • the behavior being observed is Sleep disorder. Such disorders would not be apparent to a veterinarian examining the birds during the day and/or looking for clinical signs of disease. Night sleep disorder may optionally be monitored automatically, cheaply, non-invasively, and/or continuously. Real-time information may optionally be sent to remote caretakers and/or experts. Various methods may be used to detect nocturnal activity, for example, a motion detector and/or a camera.
  • the wave length of pre-clinical outbreaks is of the order of a few days and/or may include subtle non-clinical behavior changes.
  • Convention health monitoring may be done at large time intervals that may miss the pre- epidemic outbreaks. For example, a veterinarian visiting a poultry house every few days may not observe the cyclical behavior. Often, using conventional health monitoring (for example a visiting veterinarian) will only catch the outbreak when it includes a secondary infection and/or complication. The conventional monitoring may in some cases not recognize the importance of the primary cause (for example too much light and/or noise at night and/or a preliminary low level infection and/or a minor ailment like external parasites). Alternatively or additionally, sometimes by the time conventional monitoring recognizes the problem the primary cause may have passed (for example the infection ended and/or the early susceptible animals already died off). If the primary cause is not fixed, then the secondary infection (or another secondary problem) may reoccur.
  • monitoring as described herein may optionally include observations at higher frequency than conventional methods and/or may optionally observe more subtle behavior changes than conventional methods. In some cases this may lead to recognition and treatment of the primary cause of a problem and/or a more stable solution to the problem.
  • a veterinarian may be called in at the beginning of an outbreak and use laboratory tests (for example polymerase chain reaction PCR) and/or more astute observation to find the primary cause of the problem.
  • the method described herein may recognize problems earlier than convention methods allowing more effective treatment.
  • a veterinarian may be directed to check one of the animals that showed the disturbed sleeping patterns and on examination find the parasites.
  • the predicting epidemics via observation of repeated behavioral aberrations may, for example recognize the upcoming epidemic between one and twenty days before the onset of significant clinical symptoms that would be observed by conventional monitoring.
  • Monitoring the health status of a poultry house through conventional counting and/or examining clinically sick and/or dead birds may not catch the epidemic until the thirtieth day when the pathogen has spread enough to significantly affect a large portion of the population.
  • early intervention may prevent serious damage.
  • late intervention may be much more expensive and less effective than early intervention.
  • global behaviors may be monitored along with and/or in place of individual monitoring.
  • the monitoring may be at a high temporal resolution to allow recognition of temporal patterns changes in eating behavior.
  • the average activity level of an entire flock or a large sample may be compared to other flocks and/or samples and/or to expected behavior of a flock.
  • the expected behavior of groups and/or individuals may optionally be adjusted for the breed and/or type of animal and/or the age, and or the season and/or the local climate and/or the time and/or the date and/or the altitude and/or the temperature other factors.
  • Figure 16B illustrates a case of a behavior 1624e that is constantly increasing.
  • Increase may optionally also be a sign of an outbreak.
  • the increase may be linear, exponential, and/or follow some other pattern.
  • Figure 17A illustrates an exemplary floor plan of a poultry house in accordance with some embodiments of the current invention.
  • observation may be of one or more subgroups of the population.
  • monitoring may be of animals in the vicinity of one or more local measuring stations around the house.
  • Each station may optionally sample behavior of birds in one or more local zones 1734a-d.
  • a diseases may break out starting at one area (for example zone 1734a) and spread to other areas (for example zones 1734b-d). In the area of the outbreak source, changes may become noticeable faster than when treating the poultry house as a single unit. Alternatively or additionally, spatial spreading of a behavior aberration may optionally be analyzed to indicate the beginning of an epidemic.
  • the poultry house of Fig. 17A may contain 20,000 animals.
  • the poultry house may include four sections divided by three barriers 1740. Each section may contain a more or less stable population of approximately 5,000 birds. Measuring stations may measure a behavior of the birds.
  • Optional barriers 1740 may optionally discourage and/or prevent birds from changing sections.
  • air is supplied across the entire house by an intake 1736 and exhaust 1738.
  • Water is supplied via watering devices located along optional watering lines 1732 and food is supplied by feeders 1730 spread around the house.
  • sampling stations may measure a behavioral parameter.
  • each station may measure one or more aspects of individual and/or group behavior in the local area.
  • the measurement may be visual (for example by cameras) and/or measurements may use RFID's mounted for example on animals and RFID readers mounted for example on and/or near feeders 1730 and/or watering lines 1732.
  • Figs. 17B-17E show time lapsed schematic views of the poultry house of Fig. 17A in accordance with some embodiments of the current invention.
  • Fig. 17C shows the situation seven days after Fig. 17B.
  • Fig. 17D shows the situation seven days after Fig. 17C.
  • Fig. 17E shows the situation seven days after Fig. 17D.
  • Figs 17B-17D a sample of five hundred birds amongst the 20,000 birds of the poultry house which are marked for individual observation.
  • each of the sample birds has a color coded tag and when the bird approaches a feeder a camera recognizes the bird and records how many times he puts his head down to peck at the food.
  • an RFID system could be used rather than colored tags and/or the time spent by the feeder may be measured.
  • a letter "x" represents a single bird that has aberrant behavior, for example, significantly reduction in the amount and/or intensity of the movements, and/or in the number of visits to the food.
  • reduction may be in comparison to a "normal" poultry and/or in comparison to the particular poultry's previous behavior and/or in comparison to the other marked birds in the section and/or in the entire house and/or a ranking compared to other birds etc.
  • a disease will not start uniformly in the entire house, but will be concentrated in one or more sections. For example, in Fig. 17B, a disease begins to break out in the leftmost section of the house, in the zone 1734a.
  • five birds in the vicinity of zone 1734a show aberrant behavior and seven birds in the whole house.
  • seven aberrant birds out of five hundred would not be significant and would not be recognized as a likely sign of infection.
  • Five birds out of one hundred may set off a preliminary alert. For example, the system may start making more measurements.
  • a disease will remain concentrated in one section, sometimes the disease will spread to an adjacent section and sometimes the disease will skip to a non- adjacent section. Spreading from section to section may take a few days. Sometimes spreading will be faster or slower. In some cases the disease will be distributed around the entire house and not spread from a particular area.
  • comparison will be made between sections to recognize an outbreak and/or after an outbreak is recognized. Comparing between sections can optionally locate an outbreak focus and help farmers to check better what is causing the problem in that area.
  • the disease may be a result of an environmental problem and/or a pathogen. Sometimes disease outbreaks start with sub-clinical changes of behavior that are difficult or impossible to discern by conventional observation.
  • Fig. 17C after seven days, the disease is still localized in the vicinity of zone 1734a. For example, within the section, the disease has spread such that after seven days, seven birds are showing aberrant behavior. Alternatively, small scale outbreaks may occur within a section and wax and wane. Such waxing and waning outbreaks may be a sign of a coming/developing epidemic as will be illustrated an example below.
  • Fig. 17D fourteen days after the example of Fig. 17B, in zone 1734b significant behavior aberrations have been detected.
  • nine animals are detected showing aberrant behavior in the section of zone 1734a and six nine animals are detected showing aberrant behavior in zone 1734b.
  • Spreading of a behavior from one section to an adjacent section may optionally be interpreted as a sign the aberrant behavior is due to a contagious organism and may contribute to setting off an alert.
  • zone 1734c is shown detecting three animals with aberrant behavior.
  • three animals may not be a significant number.
  • detecting aberrant behavior in three animals may be significant and may optionally contribute to the alert status.
  • the very fact that the behavior is concentrated in a particular zone may signal that it is not a random occurrence, but a sign of some kind of outbreak.
  • Figures 18A-C illustrates resulting measurements from the example of Fig. 17B- D in accordance with some embodiments of the current invention.
  • the exemplary measurement outputs of zone 1734a are shown by curve 1842a.
  • the exemplary measurement outputs of zone 1734b are shown by curve 1842b.
  • the exemplary measurement outputs of zone 1734c are shown by curve 1842c.
  • the exemplary measurement outputs of zone 1734d is shown by curve 1842d.
  • Curves 1842a-d show that, in the example of Fig. 18 A, progression of the aberrant behavior may not be a steadily growing progression, but could include a series of reoccurring peaks. In the example of Fig. 18A, the peaks are also growing over time. Either or both of these patterns (reoccurring aberrant behavior and/or progressively increasing aberrant behavior and/or spreading of aberrant behavior may be a sign of an oncoming epidemic/progressing problem).
  • Fig. 18A the reoccurring of the aberrant behavior is seen in the repeated rising and falling of curves 1842A-D.
  • the spreading of the disease is apparent, for example, from the time delay between the curves.
  • the first significant rise in that data from zone 1742a (curve 1842b) can be seen at five says days.
  • the first significant rise in aberrant behavior from zone 1742b occurs later, for example at fifteen days.
  • the aberrant behavior became noticeable after eighteen days.
  • Fig. 18B illustrates exemplary disease outbreak alert levels for the simulated data of Fig. 18A.
  • data may be interpreted according to five characteristics: the virulence of the condition the speed at which the condition is developing, the speed at which the condition is spreading, the persistence of the condition in the group and the presence of signs of a known condition.
  • An alert may for example be sent to a caretaker with summary measures: the certainty of the warning and the danger of the condition.
  • the scale of each characteristic may be assigned an integral value from 0 to 2.
  • a warning may include a certainty and/or a danger level.
  • a caretaker may be warned when there is a high certainty outbreak even if it is not notably dangerous (for example so that the caretaker can take prophylactic measures to avoid complications for example bacterial infections following minor viral outbreaks).
  • the caretaker may be warned of signs of dangerous events even when their identification and/or prediction remain uncertain.
  • the certainty index value is defined as the product of the spreading and persistence values (an aberration that continues and spreads is unlikely to be just a random occurrence).
  • Fig. 18C illustrates an alternative embodiment of an alert level scheme.
  • five properties are rated on a scale of from 1 to 5, acuteness, contagiousness, locality (how many sections have been affected), portion of the group affected, the portion recovering from the condition, the certainty that the conditions is not just a random occurrence, and a summary measure of the danger of the condition.
  • the danger level reaches two or greater a warning message is transmitted to a poultry caretaker.
  • a potentially diseased poultry may be identified, for example, if the poultry moves less than expected and/or tends to stand still or lie down more than expected, and/or walks less than expected and/or grooms himself less than expected (for example, grooming may be detected by observing grooming behavior and/or by observing the appearance of the poultry, for example feathers tend to bristle on a bird who does not groom).
  • aberrations in movement and/or distance traveled by an animal may optionally be measured, for example, by using an accelerometer, a global positioning system GPS or a local positioning system LPS, camera, visual tracking.
  • aberrant thermal transmissions may be measured, for example using a thermal camera.
  • aberrations in traffic in an animal pen may be measured.
  • behavioral changes may be used to detect environmental conditions. For example, a lack of movement in a poultry house may be a sign of the house being too hot. A tendency of the animals to huddle together may be a sign of the temperature being too cold. For example, by measuring food consumption (of individuals in a sample and/or of the whole group) cold (huddling and increased eating) may be differentiated from infections (huddling together and reduced eating). Using behavioral clues the system will permit dynamic adjustment of environmental conditions to suit livestock that is more precise than the rule of thumb methods used conventionally. For example, the temperature can be set until the optimal behavior regime is observed and not according to a fixed rule of thumb temperature (that may not be suited to all flocks, conditions and/or ages).
  • the same behavior based system may optionally be used to adjust crowding, humidity, ventilation, ammonia concentration, and/or a combination of these and/or other factors. Adjusting environmental conditions according to behavioral factors may also allow custom tradeoffs depending on for example economic factors. For example cost can be reduced in an area where fuel is expensive and labor cheap by increased floor cleaning and decreased house temperatures. 24. Data processing
  • proper processing of measurements may differentiate between healthy changes in behavior and unhealthy changes in behavior. For example, behavior changes over time in healthy animals, for example due to growth and/or maturity changes and/or due to environmental factors.
  • behavior of an animal may optionally be compared to the behavior the rest of the flock and/or of a sampled portion of the flock.
  • an animal may be denoted as aberrant if his quantity of movement is different from the mean of the sample by more than two standard deviations.
  • the behavior of the sample as a whole may be monitored. For example an alert may transmitted if the mean movement of sample mean is less than expected for a healthy group of animals. Changes in sample behavior may also be monitored, for example if the sample was above average in its quantity of movement and/or eating and began to behave like a normal flock, an alert may be transmitted.
  • data interpretation may account for individual differences. For example, an animal may be ranked within the sample group. For example, an animal that has been in the bottom of the activity ranking may not be flagged sick even though his activity is much below that expected from a "normal" animal of his age. Alternatively or additionally, an animal that has been on the top of the activity ranking may be flagged as sick if his activity drops to the middle of the ranking, even if his activity is "normal".
  • An example of the use of ranking to recognize a sick poultry is described herein below with regards to Fig. 28A-C.
  • proper timing of measurements may increase the sensitivity and/or the reliability of the measurement. For example, in some cases a sick poultry may be much less active during the day than a normal poultry. On the other hand, at night a sick poultry may be more active than other animals.
  • activity levels during the day will be computed and/or interpreted separately from nighttime activity. Separating data may make the test more sensitive (for example, the decrease in daytime activity will not be diluted out by the nighttime activity) and/or more specific (for example, a dual test may separate different conditions, for example increased nighttime activity and decreased in daytime activity may be a sign of one disease while decreased activity during both the day and night may be a sign of a different condition).
  • sampling of measurements may decrease the cost of measurement and/or data processing.
  • the sampling frequency and timing may be optimized to provide reliable while minimizing energy needed by sensors to measure and or transmit data and/or processing load.
  • movements may be measured only if the pass a certain strength.
  • the minimum G-force measured by an accelerometer mounted on the back of a chicken may range, for example, from 0.001G to 0.4G.
  • Samples may be averaged to achieve better reliability. For example, when measuring the activity level of a bird, measurements may be averaged over intervals of between 5 and 30 minutes and/or between30 minutes and 3 hours. The measurements may be made once in period of between two and three hours and/or between three hours and a daily average. The period at which the measurement is made may optionally be kept the same every day.
  • spatial sampling may be optimized. For example, traffic in a poultry house may be sampled at a few strategic locations for example, at and/or near a feeder in a poultry house and/or a fish pond. For example, pressure waves made by fish may be measured near a feeding station. Alternatively or additionally, the quantity and/or intensity of fish movements and/or pressure waves and/or crowding may be measured in the vicinity of feeders and/or other locations. Measurements may be made for example using accelerometers distributed in the water near a feeder (measuring for example movement induced in the water by the fish).
  • Crowding and distribution of animals may be measured and or compared for example between sections of a poultry house, around a feeder and away from a feeder, around a heat source and/or around a light source and/or around a water source and/or around a ventilation source and/or outlet.
  • Radar and/or sonar may be used for example to measure velocity of movements, quantity of movement in certain areas of a poultry house and/or a fish pond.
  • local and/or directional antennae and/or transmitters may be used to control the spatial sampling of measurements.
  • an accelerometer may be mounted on a fish (for example by feeding the fish a pellet containing the accelerometer and/or attaching an accelerometer to a fish [for example to his fin]).
  • data processing may be done at the sensors.
  • a sensor may compute summary statistics of data and transmit only the statistical results. Computations may be simplified, for example to save processing power or memory at a sensor.
  • Fig. 19 illustrates a few exemplary techniques to compute an activity index from measurements of acceleration over time in accordance with some embodiments of the current invention.
  • vector the accelerometer is mounted to the back of the poultry and acceleration data is measured in three dimensions.
  • the net mean vector acceleration may be approximately the acceleration of Gravity (1 G upwards).
  • Transient and mean absolute acceleration may vary as the animals travel in a chaotic fashion around the poultry house.
  • the orientation of the accelerometer with respect to gravity may changes as the poultry moves.
  • the acceleration of gravity may be along the z-axis of the accelerometer; when the chicken lies on its side, gravity may be along the y-axis; when the chicken leans forward (for example to peck at the ground), gravity may be along the x-axis.
  • absolute acceleration may be measured and/or recorded (for example the net magnitude of velocity regardless of direction). The mean absolute velocity will generally be greater than zero (unless the animal is dead and not moving) and the mean absolute acceleration may be greater than 1G.
  • Changes of acceleration may optionally be used as a measure of activity of the poultry (for example when the poultry accelerates and/or decelerates and/or when the poultry changes her orientation to gravity).
  • the sensitivity of measurements may be adjusted to detect various movements.
  • the sensitivity of the accelerometer may be adjusted to allow measurements of movements associated with changes of walking pace and/or preening and/or pecking.
  • activity may be defined as the change of the area under a curve of acceleration over time and computed, for example via by numerical integration.
  • activity may be defined as a length of the curve of acceleration vs. time, which may be measured as Sqrt[(t2-tl) 2 +(G2-G1) 2 ] where Sqrt means taking the square root.
  • data may be transmitted from an accelerometer mounted on an animal to a central data processor.
  • the raw data may be transmitted.
  • transmitting all of the raw data may take up a lot of transmitting power.
  • power may be conserved by computing an activity index at the sensor and transmitting the index value to the central unit (and not all of the data).
  • a simple index computation for example the difference between successive measurements, delta of the example of Fig. 19
  • computing power of the sensor may be conserved.
  • sensors may transmit data to the central processor intermittently.
  • a sensor may optionally send at fixed times and/or fixed time lapses.
  • the average activity may be sent every 1-10 min.
  • a sample of the raw data may optionally be transmitted along with averages and/or other processed data.
  • the sensor may transmit data whenever the quantity of data reaches a threshold.
  • data may be transmitted when a data catch becomes full.
  • data sent at fixed times may not need to include ID information (for example, the central processing unit will recognize the sender based on the time of the transmission).
  • transmission sent at non-fixed time may include ID information and/or collision detection and/or arbitration. For example, reducing the number of data transmissions may save energy and/or increase the battery life of a sensor.
  • data may be processed at the sensor. Processing may optionally reduce the amount of data transferred while preserving the ability of the system to make an accurate diagnosis. For example, data may be transmitted only for accelerations of over one G. Alternately or additionally, data may be stored at the sensor and sent a single signal with the ID may be sent only after a certain amount of movements. For example transmission of data to the central storage and computing unit may be triggered when the quantity of data stored in the sensor memory reaches a threshold. For example, data may be sent when the stored data reaches a threshold portion of the sensor storage capacity, for example when the data fills 50% of the storage capacity. An identification symbol may be sent with the data.
  • the central processor may estimate a movement and/or vitality level of a particular animal according to the number of data transmissions received from that animal.
  • the sensor may include a chip that accumulated data. The total activity and/or the average acceleration may be transmitted.
  • processed data statistics may be sent with a sample of the raw data. For example, 5-10 measurements may be made during a one second period every 10-30 seconds. Data may be sent at intervals more frequent the data averaging at the processer. The short interval data transmissions may serve to monitor for sudden collapse of the group for example due to a blast of heat.
  • a health monitoring system may be used to improve choosing of breeding stock. For example, behavior may be monitored of an animal during pregnancy and/or egg laying. Optionally animals may be bred to have stronger constitutions (for example measured as increased activity) during reproduction, pregnancy, egg bearing etc. Optionally, animals may be bred for social characteristics.
  • a monitoring system may be used to determine which animals are more susceptible to anti-social behaviors, for example fighting and/or pecking under crowded conditions and/or other conditions that sometimes occur in a poultry house or a fish pond. Such animal may optionally be bred to allow higher density animal production. Other aspects such as speed of recovery from pre-clinical infections and/or robustness of appetite and/or growth during changing conditions and/or exposure to disease may be used to breed animals that have characteristics that may not be obvious to intermittent and/or human observation.
  • a health monitoring system may be used to monitor the recovery of animals from disease. For example, when a disease has spread in poultry house, different interventions may be tried.
  • a health monitoring system may be used, for example, to estimate the effectiveness of the intervention. For example, this may allow a farmer to change an ineffective intervention before it is too late. Alternatively or additionally, different interventions may be tried in different sections of the house.
  • the monitoring system may be used to choose an intervention that is more effective and/or appropriate and/or works faster etc.
  • an emergency vaccination or drug intervention may be started and/or the poultry house may be cleaned and/or dried and/or heated to help the birds overcome the infection.
  • the poultry house may be cleaned and/or dried and/or heated to help the birds overcome the infection.
  • non-vaccinated animals are showing behavior aberrations, it may be a sign of an impending epidemic of the disease and appropriate early intervention may be taken.
  • the system can provide data for quality testing of vaccines.
  • different vaccines for example vaccines of different companies
  • animals may be vaccinated and then given mild illness, the system can be used to measure which vaccine in more effective at preventing minor disruption of health and/or welfare.
  • statistics can be accumulated over time to determine which vaccine is most effective at reducing the disruption of a poultry house due to various diseases.
  • the system can give information to help evaluate of the quality of vaccines and the materials used in them, the qualities of various genetic lines of animals that are more or less resistant to disease.
  • a sample of two hundred forty chickens in a broiler house of 20,000 chickens where mounted with a vitality meter on their backs.
  • the vitality meter included a 3D accelerometer, a processor, a memory and a transceiver and LED lights.
  • the data included the average activity level (average acceleration) during the lhour period.
  • raw acceleration data or processed data for the last five minutes of each 1 hour sampling period was loaded to the server.
  • the raw data was used to determine the animal's health state (for example, walking, running, preening, and/or lying). At times the raw data was also downloaded on demand, for example when it was desired to track states of a particular bird.
  • the server optionally, computed activity level and rank chicken of each chicken in the virtual flock of the four hundred sampled chickens every hour. If there was a significant change in the chicken's activity and/or rank an alert was transmitted to a caretaker. For example, an alert was transmitted if a chicken's activity fell to two standard deviations below the average for the virtual flock. For example, an alert was transmitted if a chicken's activity rank fell at least two places for three hours consecutively. When the caretaker deemed necessary he called for a veterinarian and/or a breeder.
  • transmissions for different chickens were spread in time. For example, if one chicken sends data at 6:00, the next chicken sends data at 6:01 and another at 6:02 etc. Along with reporting hourly average vitality, the average vitality in the last five minutes was included in each transmission. Thus, every five minutes there was data available on at least five chickens in the last ten minutes. This may provide advanced warning of acute emergency conditions (for example if the fans break down a fast change in vitality will be observed and a caretaker may intervene).
  • the caretaker when it was desired to examine a particular chicken (for example after an alert for low activity of the chicken) the caretaker activated an optional remote controlled LED light mounted on the chicken for easy identification.
  • Identification tags and sensors were optionally mounted to chickens with a remote release mechanism (for example an electromagnet and/or motor and/or knot with a release and/or cutting mechanism) operated through the central processor.
  • the caretaker could optionally cause the tag of any and/or all of the chickens to be released, for example to fall to the floor.
  • the LED was also optionally used to find and recover fallen tags.
  • Figs. 20A-D illustrate the one second averaged acceleration results for various states of chickens in accordance with some embodiments of the current invention.
  • Fig. 20A illustrates acceleration typical for a chicken while drinking.
  • Line 2060 illustrates the acceleration in the z (vertical) direction.
  • Lines 2061 and 2062 illustrate acceleration in the x and y (horizontal directions).
  • accelerometers were mounted with the x-axis along the longitudinal axis (forward and backward) of the chicken and the y-axis along the lateral axis of the chicken.
  • measurements were made at a rate between, for example, 5 and 10 measurements per second on each axis during a one second measurement period every 10 to 20 seconds.
  • the chicken dips his head to drink and/or shakes himself.
  • Fig. 20B illustrates acceleration typical for a chicken while eating (from 1 sec until 400 seconds) and preening (from 400 sec to 600 sec).
  • Fig. 20C illustrates acceleration typical for a chicken while walking.
  • FIG. 20D illustrates acceleration typical for a chicken while sleeping. At points 2066 the chicken rolls over.
  • a state of the chicken may be distinguished from acceleration data. For example, in the example, for accelerometers on the chicken's back, if the average acceleration is higher in the x-direction than the z-direction this may be taken as a sign that the chicken is eating, cleaning feathers (for example, his head is down pecking the floor and therefore gravity appears to be in the x-direction). For example, if there are few small changes in acceleration, but occasional switches along all the axes, the chicken may be sleeping (for example she is moving very little and acceleration changes are due to occasionally reorientation of the axes with respect to gravity when she rolls over in her sleep). For example, if there is a lot of activity and the effect of gravity remains steady in the z-direction, the chicken may be walking etc.
  • the majority of movement was in the vertical directions. Therefore accelerations magnitude could be predicted by just measuring vertical movements. Nevertheless, measuring 3D acceleration was found to have a few advantages over measuring just vertical acceleration. For example, sometimes the meter may become move on the chicken and become disoriented. When measuring on only one axis this would give false results whereas measuring on three axes and computing the absolute magnitude may give more robust results.
  • the magnitude may be averaged over multiple measurements and/or a time period. For example, the differences between the different axes may be useful in figuring out the state of the chicken. For example one may differentiate eating from walking because the dominance of vertical movement is more pronounced during walking than during eating.
  • Fig. 21 illustrates an example of changes in activity of a twenty four day old chicken over a day in accordance with some embodiments of the current invention.
  • Fig. 21 quarter hour averaged acceleration values are shown.
  • the chicken is less active at night 2150a.
  • the chicken is most active in the morning 2150b.
  • the chicken is active in the afternoon 2150c and evening 2150d.
  • Fig. 22A illustrates acceleration measurements (one hour averages) for four chickens over a week in accordance with some embodiments of the current invention.
  • the abscissa represents the activity level of the individual chickens.
  • activity level is defined as the absolute magnitude of acceleration.
  • the measurements were normalized by subtracting the average of all of the sampled chickens and dividing by the standard deviation of the activity level.
  • the ordinate axis is marked by the age of the chickens days :hours: minutes.
  • the sample average is shown as a line of magnitude zero 2280.
  • the normalized activity levels 2281a,b,c of three healthy chickens are shown oscillating close to the zero 2280 line.
  • the activity 228 Id level of a fourth chicken that became sick during the period is also shown.
  • the sick chicken can be recognized by his reduced activity level 2281d.
  • the reduced activity is already apparent at age 32 days when his activity level is consistently between one and two standard of deviation below the average. By 34 days his activity level is consistently at least two standard deviations below the average.
  • Fig. 22B illustrates the acceleration measurements of Fig. 22A without normalizations. The average and difference of the absolute magnitude can be seen.
  • Fig. 23A illustrates the normalized activity level 2381 and test results of an example of a chicken that was exposed to a chronic illness at age of approximately 28 days.
  • Fig. 23B marks failures of each of 23 tests shown as an open circle 2382. On the abscissa is marked the test number. The animal died 2383 at age 39 days.
  • Tests used to recognized extreme behavior aberrations chickens included, for example some or any of the below tests:
  • the above tests represent a high confidence indicator of disease and any one may trigger an alert to a caretaker.
  • Lower confidence warnings may be issued for less extreme aberrations. For example a warning may be issued for any negative slope which lasts for more than 3 days.
  • tests 13 and 14 may represent a hyper-acute condition taking effect within two days or less.
  • tests 15-17 may represent an acute condition taking effect within three to five days.
  • tests 18-22 may represent a medium term condition taking effect in six to ten days.
  • test 23 may represent a chronic condition taking more than 10 days to become apparent.
  • the tests may detect changes in apparently normal behavior.
  • a chicken may not have clinical symptoms of illness and may not display any particular abnormal behavior (for example coughing or fluffed feathers).
  • the chicken may nevertheless be, for example, slightly less active than normal and/or slightly less active than a previous day.
  • the changes may include for example statistical changes in normal behavior.
  • the change in behavior may, for example, not be apparent to an observer walking through the poultry house (for example the observer may not know whether the chicken is resting now after a day of activity or whether she has been uncharacteristically resting all day).
  • Such unapparent changes in activity may be for example early signs of the beginning of an illness and/or they may be for example due to a minor illness.
  • tests for recovery may include tests similar to those listed above for disease and negative conditions.
  • tests for recovery may include tests the opposite of those listed above (for example 1. a single point above three standard deviations from the sample average; 2. Nine consecutive points are above the sample average; an increase in activity, slope of greater than 0.014 over last 11 days).
  • Fig. 24A illustrates the normalized activity level 2481 and test results of an example of a chicken that was exposed to an acute illness at age of approximately 30 days in accordance with some embodiments of the current invention.
  • Fig. 24B marks failures of each of 23 tests shown as an open circle 2482. On the abscissa is marked the test number. The animal died 2483 at age 36 days in accordance with some embodiments of the current invention.
  • Fig. 25A illustrates the normalized activity level 2581 and test results of an example of a chicken that was exposed to an acute illness at age of approximately 28 days in accordance with some embodiments of the current invention.
  • Fig. 25B marks failures of each of 23 tests shown as an open circle 2582. On the abscissa is marked the test number. The animal recovered 2583 at age 36 days in accordance with some embodiments of the current invention.
  • Figure 26 shows and example of reoccurring behavior changes preceded an outbreak of a viral infection complicated by a bacterial infection in the exemplary poultry house in accordance with some embodiments of the current invention.
  • the abscissa represents the number of birds moving from a healthy state to a sick state on a given day and the ordinate represents the age of the flock.
  • all sentinel were considered healthy at the beginning of the observation; a healthy chicken was considered to move to a sick state if he failed at least one of the 23 test (listed above) in eight consecutive 1 hour time periods; a bird who was in a sick state was considered to have returned to the healthy state if he did not fail any test for two consecutive days.
  • the graph of Fig. 26, may be used to test the contagiousness and/or spreading of a condition.
  • treatments and/or laboratory tests and/or other measures may have been started by the 29 th and/or 31 st day. On the 33 rd and 34 th days there occurred a larger increase 2624c of failures affected twelve new birds each day. Accounting for the previous two outbreaks, the pattern of growing repeated outbreaks may optionally activate a critical warning and/or emergency intervention on the 33 day. Such an occurrence without knowing about the previous two waves of infection may optionally have activated a mild warning.
  • wavelike increasing and decreasing of a change in behavior may be interpreted as a sign of an oncoming infection. In some embodiments increasing sized waves of behavior changes may be interpreted as a sign of an oncoming disease outbreak and/or other condition. In some embodiments further tests may be made to determine the particular cause of the change of behavior.
  • Figure 27A shows total number of tests failed for the same exemplary poultry house as fig. 26 in accordance with some embodiments of the current invention.
  • the abscissa represents the total number of tests failed by the virtual flock and the ordinate represents the age of the flock.
  • the graph of Fig. 27A showing the total number of tests failed, shows a combination of the virulence of the condition and its contagiousness.
  • a condition when a condition is defined as a disease outbreak may depend on the nature of the symptoms. For example, in a poultry house, an infection with obvious systems, for example serious difficulty breathing, may become apparent to a caretaker when more than 5-10% of the animals are sick. For such a disease 5-10% infection rate may optionally be defined as the beginning of an outbreak. For example in the example of Figs. 26, 27A,B the caretaker noticed the infection when about twenty of the 240 sentinels (about 8%) where sick. Alternatively or additionally, for a disease having less serious symptoms, for example, mild difficulty breathing, a conventional observer may not notice the disease until 10-30% of the animals are affected. Optionally for a disease with mild symptoms a 10-30% infection rate may be defined as a disease outbreak. Some embodiments of the current invention may detect changes in behavior that precede an outbreak, for example when they affect 1-2% of the population.
  • a disease may be apparent to a conventional observer and/or an outbreak may be declared depending on the mortality rate. For example, an outbreak may be declared if more 3 to 5 chickens per thousand chickens die each day. The disease may, for example be apparent to a conventional observer and/or an outbreak declared if more than 5 per thousand die in one day and/or if more than three per thousand die on two consecutive days and/or if more than 2 per thousand die on three consecutive days.
  • Fig. 27A the presence of health problem was already noticeable by the vitality measurements of an exemplary embodiment the current invention on the 27 th day and was clearly recognizable by the 33 day.
  • the upcoming outbreak could for example be recognized between one and six days before being recognized by a skilled caretaker.
  • Fig. 27B illustrates the cumulative number of chickens failing at least one test in the poultry house of Figs. 26 and 27 A.
  • the number of newly sick chickens is similar (within 20%) to the total number of sick chickens one might conclude that the disease is in a lag phase or in a steady state. Because there are continuing waves of increasing amplitude (first 7 chickens then 9 chickens), one might conclude that the disease is spreading. This may set off, for example a mild or a medium level alert. Optionally an alert may be issued even when the disease appears to be in the lag phase.
  • the cumulative number of sick chickens (for example 11 at the transient increase 2724d') remains higher than the number of new cases (for example 6 at the transient increase 2624d).
  • the new cases may be interpreted as continued spreading of some infection [maybe a viral infection that was a precursor and/or complication of the bacterial infection] and/or a new infection).
  • the continued higher value of cumulative sick birds may indicate that at least in some birds, recovery is slow.
  • the exemplary embodiment of a monitoring system detected a transient increase 2624d, 2724d, 2724d' of behavior aberrations during the recovery period.
  • Such changes in the state of the sentinels may be an early signal, for sign, of reinfection and/or complications of a previous infection and/or an opportunistic new infection affecting the weakened birds.
  • Conventional observation may be unlikely to pick up on a small change in sick birds when there are previously sick birds present (for example a increase 2624d, 2724d, 2724d' and/or the continued spreading to new birds during the recovery period).
  • the monitoring system may optionally detect and/or quantify such spreading and/or changes and/or allow for early and/or prophylactic treatment to avoid such complications.
  • Fig. 28A-C illustrate a histograms the area under the graph of acceleration of a sample of chickens in a poultry house in accordance with some embodiments of the current invention.
  • the abscissa represents the quantity of movement (the side of the graph represents right more movement /vitality more healthy chicken, the left side of the chart represents less movement/vitality less healthy chicken) the ordinate represents the number of birds in each vitality bin.
  • acceleration was sampled at a rate of five measurements per second and interpreted by summing deltas as described above.
  • a greater quantity of movement means a greater difference between successive acceleration measurements which may be interpreted as stronger movements.
  • Figs. 28A-C the white bar shows the place of a particular sentinel chicken
  • FIG. 28A chicken 2863 is shown in a healthy state. It is seen that chicken 2863 is a particularly active bird well towards the top of the histogram.
  • the histograms show the change over time of the relative position or rank of chicken 2863 within the sample of sentinels.
  • the histogram is the activity level (this can include for example the amount accumulated of movement in general and/or the cumulative distance walking, the average speed of walking, cumulative time eating or anything characterizes the activity of birds).
  • Fig. 28B shows the histogram two days after chicken 2863 was exposed to the infection (at 34 days). Chicken 2863 still displays apparently normal behavior (towards the middle of the histogram). Nevertheless, chicken 2863 shows a significant reduction is ranking (no longer at the top of the histogram).
  • Fig. 28C shows the histogram at 36 days, four days after Fig. 28A.
  • Chicken 2863 is still in the range of normal but shows a very distinct and consistent reduction in ranking. Thus a conventional observer would not recognize chicken 2863 as sick until well after 36 days whereas by tracking the ranking of chicken 2863 by the method of the current application it may optionally be possible to recognize the disease earlier (by the 34 day or even before).
  • Ranking may optionally be used to track the improvement of chicken during treatment. Animals may be ranked in any measured parameter, for example, activity, number of movements, intensity of movement time spent eating/drinking, amount food/water ingested, amount of time eating/walking/preening, distance walked etc.
  • Figure 29 is a block diagram illustrating an exemplary embodiment of a system for early detection of conditions affecting a flock of livestock in accordance with some embodiments of the current invention.
  • the system may include a sensor 2990.
  • Sensor 2990 may include, for example, an accelerometer, an optical sensor (for example in the visible and/or infra red spectrum), an audio sensor (for example a microphone), a chemical sensor (for example an ammonia sensor), a weight sensor (for example sensing the weight of a chicken and/or the weight of feed) and/or a RFID sensor.
  • a sensor 2990 may be, for example, mounted on an animal and/or fixed in an animal pen and/or mobile.
  • Sensors 2990 may optionally be connected to a transceiver 2992a. Sensors 2990 may optionally be connected to a transceiver. Transceiver 2992a may optionally be used to transmit data from sensor 2990 to a transceiver 2992b of a central processor 2998 and/or a transceiver 2992c user interface 2994 of a caretaker. Alternatively or additionally transceiver 2992a may be used to receive commands from a transceiver 2992b of a central processor 2998 and/or a transceiver 2992c of a user interface 2994 of a caretaker. Central processor 2998 may include a memory 2996. Alternatively or additionally sensor 2990 and/or user interface 2994 may include a processor and/or a memory.
  • the system may include a marker 2999a associated with sensor 2990 and/or a marker associated to an animal 2999b.
  • Markers may include a passive marker, for example an optical marker (for example a colored mark) and/or an active marker (for example a radio and/or optical beacon).
  • the active marker may include an LED and/or a loudspeaker and/or a radio beacon.
  • the beacon may include a RFID device.
  • the beacon may be activated by a signal, for example from user interface 2994 and/or from processor 2998 and/or sensor 2990. Alternatively or additional the beacon may be activated automatically, for example when it falls of an animal and/or when an animal displays a behavior aberration and/or or when a sensor malfunctions.
  • compositions, method or structure may include additional ingredients, steps and/or parts, but only if the additional ingredients, steps and/or parts do not materially alter the basic and novel characteristics of the claimed composition, method or structure.
  • a compound or “at least one compound” may include a plurality of compounds, including mixtures thereof.
  • range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.

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Abstract

Un système et un procédé de prédiction précoce et/ou de détection précoce d'états affectant une population d'élevage et/ou pour effectuer le suivi un état du bétail peut consister à effectuer le suivi du comportement d'individus sentinelles identifiés précédemment dans un échantillon de la population d'élevage ne permettant pas de distinguer certains individus. La localisation peut se faire éventuellement au moyen d'un capteur optique. Dans certains modes de réalisation, une sentinelle non identifiée peut être suivie et/ou une sentinelle non identifiée peut être à nouveau identifiée et/ou des sentinelles peuvent être marquées. Dans certains modes de réalisation on peut effectuer le suivi d'un comportement dans la population et détecter un état la population sur la base d'un motif de changements dans le comportement. Le comportement peut être éventuellement suivi chez des individus et/ou un échantillon et/ou un troupeau virtuel. Le procédé peut être utilisé éventuellement pour la détection précoce d'une épidémie d'une maladie, pour améliorer une technique d'élevage et/ou pour développer des traitements et/ou vaccins.
PCT/IL2014/050122 2013-02-04 2014-02-04 Système d'alerte précoce et/ou de surveillance optique d'une population d'élevage comprenant de la volaille WO2014118788A2 (fr)

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