EP4637338A1

EP4637338A1 - System and method for monitoring at least one animal in a dairy farm comprising a plurality of zones

Info

Publication number: EP4637338A1
Application number: EP23833228.2A
Authority: EP
Inventors: Cristian VERGARA MUR
Original assignee: DeLaval Holding AB
Current assignee: DeLaval Holding AB
Priority date: 2022-12-21
Filing date: 2023-12-15
Publication date: 2025-10-29
Also published as: CN120302882A; WO2024136732A1

Abstract

The disclosure relates to systems and methods for monitoring at least one animal (100), such as at least one cow, in a dairy farm (1) comprising a plurality of zones. Animal location data (P) comprising in which zone (Z) of the plurality of zones the at least one animal (100) was located at certain moments in time is determined by animal localising means (200). Furthermore, at least one respective response (R) from the at least one animal (100), indicative of a level of physical and/or psychological stress and/or discomfort of the at least one animal (100) at certain moments in time, is registered by at least one animal sensor arrangement (300). At least one respective response (R) from the at least one animal (100) is associated with the corresponding animal location data (P) by a control unit (20) to determine in which zone (Z) said at least one animal (100) was located at the certain moment in time on which said at least one respective response (R) was registered. A zone-specific stress level (Sz) for a zone (Z) is determined by the control unit (20) based on at least one respective response (R) and an action is triggered by the control unit (20) if the zone-specific stress level (Sz) fulfils a stress level criterion (Sc).

Description

SYSTEM AND METHOD FOR MONITORING AT LEAST ONE ANIMAL IN A DAIRY FARM

COMPRISING A PLURALITY OF ZONES

TECHNICAL FIELD

The invention relates to systems and methods for monitoring at least one animal, such as at least one cow, in a dairy farm.

BACKGROUND

Stress will negatively impact animals at a dairy farm in different ways. One negative effect is that the reflex known as "milk let down", driven by oxytocin hormone, is impaired. Stress, thus, leads to a reduced milk yield and, consequently, a lower profitability of a dairy farm. Stress is also an indication of the wellbeing of the animals concerned. It is, thus, of interest for a farmer to monitor the stress levels within the herd of his/her dairy farm.

There are various prior art systems for monitoring stress of an animal at a dairy farm, e.g. by measuring rumination activity or movements of the animal. However, there is a need for an improved system providing a more comprehensible output of the stress levels among animals at a dairy farm.

SUMMARY

It is an object of the invention to alleviate some of the shortcomings of prior systems and methods for monitoring stress of animals at a dairy farm. Stress should herein be interpreted as a physical, emotional or psychological strain and/or an absence of comfort.

According to one aspect of the invention, the object is achieved by a system for monitoring at least one animal in a dairy farm, wherein the dairy farm comprises a plurality of zones, each zone being associated with a respective unique zone label. The zones are to be interpreted as different areas or spaces serving various functions at the dairy farm and of which at least some comprise various assets. Examples of zones are milking zones (comprising e.g. one or more stanchions, milking stalls, milking robots, rotary milking platforms or any other type of milking equipment), pre-milking zones (where animals are held waiting to be milked, also known as holding area, waiting area, holding pen), resting zones, feeding zones, pasture zones, walking alleys etc. A zone may also be interpreted as a sub-area of an area or space at a dairy farm. An example of such a zone is one milking stall, one bail on a rotary platform or one milking robot in a milking zone. The system comprises animal localising means which is configured to determine animal location data, wherein the animal location data comprises in which zone of the plurality of zones the at least one animal was located at certain moments in time. In other words, the unique zone label for the zone within which the animal of interest was located at the certain moment in time of interest is comprised in the animal location data.

The system further comprises at least one animal sensor arrangement for registering at least one respective response from the at least one animal, which response is indicative of a level of physical and/or psychological stress and/or discomfort of the at least one animal at certain moments in time. The registered at least one respective response may be seen as indicative of the level of wellbeing or ease of the at least one animal concerned. The system further comprises a control unit configured to receive or determine the respective response and animal location data, and associate the respective response from the at least one animal with the corresponding animal location data for the same at least one animal for determining in which zone said at least one animal was located at the certain moment in time on which said respective response was registered. Corresponding in this context means a response and animal location data for an animal which are time stamped with the same, or substantially the same, moment in time. Due to the zoning of the layout of the dairy farm and since both the animal location data and the respective response from the at least one animal is determined and registered, respectively, for certain moments in time, the responses and animal location data will be provided with a time stamp. The animal location data will comprise a time stamp of the time when the at least one animal was located in a zone, together with the unique zone label of said zone. The respective responses will comprise a time stamp with the respective time at which the respective responses were registered from the at least one animal. Thus, the control unit can establish which animal location data corresponds to which respective response by utilizing the time stamps. When associating a response with corresponding animal location data, the zone label comprised in said corresponding animal location data may be assigned to said response. Consequently, the control unit can determine the whereabouts of the at least one animal for each registered response from that animal.

The control unit is further configured to determine a zone-specific stress level for the zone, in which the at least one animal has been located, based on at least one respective response which has been associated with that zone and trigger an action if the zone-specific stress level fulfils a stress level criterion. Thereby, monitored stress levels are automatically related to the different zones of the dairy farm. Dairy animals, such as cows, are exposed to different external stressors in different zones of a farm. Such external stressors may, for example, be unexperienced personnel treating the animals in an incorrect or crude manner, newly introduced machines, noise, machinery interaction such as attaching milking cups to the teats of the animals, too high or low temperature, weather conditions, uncomfortable conditions such as hard floors, slippery floors and/or crowding. By the above-described aspect of the invention, zones of the dairy farm which induce stress on animals can be identified by associating, i.e. connecting/linking/ pairing, the location of the animal with responses indicative of stress from that animal.

By monitoring stress levels in zones of a dairy farm by the system described herein, a user of the system may identify zones which are stressful for the animals at the dairy farm or zones where the stress levels have increased compared to previous measurements. The user may investigate the reasons to relatively high stress levels and carry out measures to fix or at least try to alleviate any problems. Such measures, which are of course dependent what problems that are inducing stress, may e.g. be training personnel, reducing noise, increasing comfort, reducing time spent in stressful zones, altering temperature, decreasing the number of animals within stressful zones, etc. A fixed problem will lead to decreased stress levels and, consequently, a higher productivity/milk yield. This, in turn, leads to a more sustainable milk production since a higher milk yield per animal leads to less environmental contamination per unit of milk.

The control unit of the system comprises a processing circuit configured for performing various calculations to conduct the various tasks described herein, such as e.g. associating responses and animal location data, the determining of zone-specific stress levels, the triggering of an action, etc. Such processing circuit may comprise one or more instances of a processing circuit, i.e. a Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC), a microprocessor, or other processing logic that may interpret and execute instructions. The control unit may include a plurality of processing circuits, such as, e.g., any, some or all of the ones enumerated above.

The control unit may be able to determine or receive from the at least one animal sensor arrangement and/or the animal localising means information uniquely identifying the at least one animal for which animal location data and responses is determined/registered. Such information may comprise an identity reference such as a locally or globally unique number, name, and/or code, etc. The control unit may further be configured to receive or determine the time stamps comprised in the responses and animal location data, i.e. time references, such as a highly accurate clock signal, indicating which certain moment registered responses and determined animal location data appertains to.

Furthermore, the control unit may comprise a memory in some embodiments. The optional memory may comprise a physical device utilised to store data or programs, i.e., sequences of instructions, on a temporary or permanent basis. According to some embodiments, the memory may comprise integrated circuits comprising silicon-based transistors. The memory may comprise e.g. a memory card, a flash memory, a USB memory, a hard disc, or another similar volatile or non-volatile storage unit for storing data such as e.g. RAM, ROM (Read- Only Memory), PROM (Programmable Read-Only Memory), EPROM (Erasable PROM), EEPROM (Electrically Erasable PROM), etc. in different embodiments.

The at least one animal sensor arrangement may comprise a rumination sensor arrangement and the at least one respective response from the at least one animal may comprise a rumination activity of the animal. Rumination is the process of regurgitation of feed from the rumen to mouth of a ruminant animal followed by remastication and reinsalivation, and then swallowing and returning of the material back to the rumen. Rumination is found to be voluntarily controlled by ruminant animals where they will decrease its rumination activity or stop to ruminate if it is disturbed. Furthermore, an increased stress level, e.g. due to events that results in pain, discomfort, hunger, fear, anxiety, illness etc., is also related to a drop in rumination activity. The rumination activity of the animal is, thus, indicative of a level of physical and/or psychological stress and/or discomfort, although negatively correlated meaning that a low rumination activity indicates a high stress level while a high rumination activity indicates a low/normal stress level.

The rumination sensor may be a tag attached to the animal, such as to the ear, neck or head of the animal. The tag may comprise an accelerometer for repeatedly sensing acceleration. The accelerometer may be a 3-dimensional (3D) accelerometer, also called 3-axis accelerometer, comprising three separate internal accelerometers mounted substantially orthogonally in relation to each other, allowing analysation of separate components of complex accelerations. Each accelerometer is an electromechanical device used to measure acceleration forces. Such forces may be static, like the continuous force of gravity, or dynamic to sense movement and/or vibrations of the animal. The tag comprising an accelerometer may be attached to the animal such that movement of the tag, and thus the acceleration measured by the accelerometer, is at least partly correlated to the movement of a body part of the animal, such as the jaw, neck, ears or head, during rumination. There are known rumination sensors which have these described functions, such as ear-attachable tags which registers rumination activity in the form of ear movement recorded via a three- dimensional accelerometer and the rumination sensor described in patent EP 3 188 592 B1.

The rumination sensor may as an alternative or additionally comprise a microphone attached to the animal such that the rumination activity may be registered by recording sounds from the animal. The microphone may be incorporated in a neck collar attached tightly onto the neck of an animal such that the sounds from e.g. regurgitation of boluses during rumination can be recorded.

A third example of a rumination sensor suitable for use in the system is a halter which comprises strain or pressure gauges for registering jaw motion during rumination. A fourth example of a rumination sensor is a camera directed towards the animal such that it can register contractions at the location of the rumen triangle.

The rumination activity registered by the rumination sensors may, in the simplest form, be a response comprising whether the animal is ruminating or not at the certain point in time on which the registering occurs. Another parameter which may represent the rumination activity may be the number of rumen contractions and/or ruminant boli per time unit or the total registered number of rumen contractions and/or ruminant boli during a time-period based on a plurality of responses which has been associated with the same zone. The amount of mastication or rumination movements may be a further or additional parameter representative for the rumination activity. A rumination ratio for an animal may also be representative for the rumination activity. This may be registered by registering a plurality of responses associated with the same zone during a time period and divide the responses indicating that rumination occurred with the total number of registered responses (the total number being both responses where rumination occurred and responses where rumination did not occur). This ratio may further be used to estimate the time spent ruminating during the time period, which may alternatively or additionally represent the rumination activity, by multiplying the time period by the rumination ratio. The time spent not ruminating during the time period may, of course, be estimated by subtracting the time spent ruminating from the time period.

When determining the at least one zone-specific stress level, the control unit need to account for rumination activity being negatively correlated to stress. The time spent not ruminating can be used as a value for the zone-specific stress level without any conversion. For the other parameters mentioned above, simple calculations may be used to translate them into a zone-specific stress level, such as dividing a “normal” rumination activity with a registered rumination activity, by subtracting a registered rumination ratio from 1, by dividing 1 by the registered rumination activity, etc. The resulting value from these calculations may represent the at least one zone-specific stress level.

The at least one animal sensor arrangement may alternatively or additionally comprise a head movement sensor and the at least one respective response may comprise head movements of the at least one animal. Head movements of the animal is indicative of a level of physical and/or psychological stress and/or discomfort, where upwards head movements or keeping the head up high is positively correlated with stress, meaning that if many such movements occur or heads are kept high during long time periods it is indicative of a high stress level. The expression "upwards head movement" is to be interpreted as a head movement from a low position to a high position, e.g. where the animals head is moved from below a backline of the animal to a position above the backline. The expression "keeping the head up high” is to be interpreted as keeping the head above a certain height e.g. in relation to the backline of the animal, to the ground, or in relation to a height which the animal holds its head when being calm.

The head movement sensor may be a tag attached to the animal, preferably to the head or close to the head, such as to the ear, neck or horns. Such a tag may comprise a motion sensor, e.g. a 3D-accelometer, a gyroscope or other similar sensor for detecting movements and directions of movements made by the tag and, consequently, the head of the animal.

At least one camera directed towards the animal may also or alternatively be utilised as a head movement sensor. The camera may be e.g. a stereo camera, an infrared camera, a video camera, a radar, a lidar, an ultrasound device, a time-of-flight camera, a Passive Infrared (PIR) sensor or similar device, in different embodiments. The camera may capture images, such as e.g. a sequence of images and/or a video sequence of the heads of the animals and by image recognition/computer vision and object recognition, upwards head movements of the animals and/or heads being held up high may be detected and registered.

Thus, the at least one zone-specific stress level can be readily determined by the control unit since the head movements described above is positively correlated to stress. The at least one zone-specific stress level may e.g. be time spent keeping the head up high during a time period or number of upwards head movements during a time period based on a plurality of responses associated with the same zone.

The at least one animal sensor arrangement may additionally or alternatively comprise a heart rate sensor and the at least one respective response from the at least one animal may comprise a heart rate of the at least one animal. The heart rate of an animal is positively correlated with stress where an increased or relatively high heart rate is indicative of an increased or relatively high stress level. The heart rate sensor may be a band with a heartbeat meter. Such a band may be attached on the animal, preferably close to an artery, e.g. around the leg, abdomen, neck or any other suitable body part. A heartbeat meter included in a tag attached to the animal, such as to the ear of the animal, is also feasible. When a heart rate sensor is used, the at least one zone-specific stress level may e.g. be heart beats per minute based on a plurality of responses associated with the same zone.

The invention is not limited to the sensors explicitly mentioned above. Any sensor capable of registering a response from an animal which is indicative of a level of physical and/or psychological stress and/or discomfort may be used in the system described herein. Other examples of sensors are pedometers, blood pressure sensors, thermometers for determining body temperature of the animal, breathing/panting sensors, ear movement sensors (e.g. an ear-tag comprising a motion sensor) to register ear movements, sensors for registering cows bunching (e.g. a positioning system or a camera), etc.

Pre-processing and/or additional processing of the responses registered by the sensors described above may be needed to facilitate the determining of the zone-specific stress level, such as e.g. image recognition, computer vision, object recognition, sorting or filtering data, etc. Such pre-processing or additional processing may be performed in the control unit of the system mentioned above, in a separate unit comprising processing means or in an additional unit comprising processing means included in the at least one animal sensor arrangement.

The animal localising means may comprise a Real Time Location System (RTLS) configured to determine an identity reference of the at least one animal and the respective position of the at least one animal at certain moments in time, e.g. as coordinates in a coordinate system. The RTLS may comprise a tag attached to the animal and a set of base stations, wherein each base station in said set is configured to receive a wireless signal transmitted from the tag. The wireless signal may comprise an identifier uniquely identifying the tag, and thus the animal to which it is attached, i.e. an identity reference such as a locally or globally unique number, name, and/ or code, etc. The wireless signal may be transmitted between the tag and the base stations via any convenient wireless communication technology such as Ultra-Wide Band (UWB), Bluetooth (BT), Wireless Universal Serial Bus (Wireless USB), Radio Frequency Identification (RFID), Wi-Fi, etc.

Each base station may be configured to forward a respective tag message describing the received wireless signal to either the control unit described above, a separate unit comprising processing means or an additional unit comprising processing means included in the animal localising means. The control unit, the separate unit comprising processing means or the processing means included in the animal localising means may in turn be configured to receive the tag messages, e.g. via a transceiver, and based on tag messages received from at least three base stations determine the respective positions for the animal tag, and thus the animal, e.g. as coordinates in a coordinate system, at certain moments in time. The positions may be determined via e.g. triangulation or trilateration in at least two directions, e.g. two perpendicular directions.

Furthermore, the dairy farm may be associated with a representation of the plurality of zones, stored in e.g. a database or any other data storage. In which zone of the plurality of zones the at least one animal is located at certain moments in time may be determined by comparing the representation of the plurality of zones with determined respective positions, e.g. by a RTLS, of the at least one animal at certain moments in time.

The representation of the plurality of zones may for example be a CAD-model, a digital twin of the dairy farm or any structured data in a local or global coordinate system. The system may comprise a user interface comprising a graphical user interface (GUI) configured to display a layout of the dairy farm. The user interface may also be configured to obtain usergenerated commands, e.g. with support from the GUI, via zone-defining instructions in relation to the layout of the dairy farm, which zone-defining instructions specify the desired zoning of the farm and the corresponding zone labels. Thus, a user may define different zones of the dairy farm in a simple and intuitive manner.

The representation of the plurality of zones may comprise sets or ranges of coordinates, wherein each set or range of coordinates is representative of a zone and associated with the unique zone label of that zone. Each set or range of coordinates may e.g. be coordinates along a perimeter representing the respective perimeter of each of the plurality of zones or intervals of coordinates representing the area which the zone covers in a coordinate system. The positions of the at least one animal as determined by the RTLS may be represented as coordinates in the same coordinate system as used for the representation of the plurality of zones. The animal location data may be readily determined by the animal localising means by comparing the set of coordinates representative for the zones with the coordinates representing the position of the at least one animal at certain moments in time. This comparison may be performed in the control unit (in a case where the control unit is considered as a part of the animal localising means), a separate unit comprising processing means or an additional unit comprising processing means included in the animal localising means.

Another option is that the area of the dairy farm is associated with a regular pattern of positions, such as e.g. coordinates in a coordinate system, in which each position in this regular pattern is unambiguously associated with a particular zone and the unique zone label of that zone. The control unit (in a case where the control unit is considered as a part of the animal localising means), a separate unit comprising processing means or an additional unit comprising processing means included in the animal localising means may be configured to determine a nearest position in the regular pattern of positions, which nearest position is the position in the regular pattern of positions which is located at the shortest Euclidean distance from the position of the at least one animal as determined by a RTLS. The animal location data is thus determined by the animal localising means since the determined nearest position of the regular pattern of positions is unambiguously associated with a particular zone. The regular pattern of positions may contain a rectilinear equidistant dots pattern that covers the area of the dairy farm. In other words, the regular pattern of positions may be represented by a set of dots organized in such a manner that each dot is located in a respective intersection of a Cartesian grid. This highly facilitates the process of finding the position in the regular pattern of positions that is the nearest position to the position of the at least one animal as determined by a RTLS.

By the above-described options, the correct zone label is assigned to the animal location data being determined, and the control unit subsequently associates the determined animal location data with the corresponding respective response from the at least one animal.

The animal localising means may alternatively or additionally comprise animal identification means associated with at least one zone at which the animal identification means is arranged. This setup may be used on a dairy farm wherein at least one zone of the plurality of zones of the dairy farm is physically separated from other zones and comprises a passage arrangement, wherein the passage arrangement comprises an entry passage and an exit passage for entry to and exit from the at least one zone. The at least one zone being physically separated from other zones such as to avoid that an animal is entering or exiting the zone without passing the gate arrangement. The animal identification means may comprise any device capable of identifying an animal, such as readers configured to read ID- tags attached to the animals, wherein the ID-tags have an identity reference uniquely identifying the animals and/or cameras with processing means that utilizes image recognition techniques to identify animals by e.g. recognising different body parts or patterns of the animals. The animal identification means may be configured to identify the at least one animal upon entry through the entry passage and upon exit through the exit passage.

By registering moments in time on which an animal entered and exited a zone, the animal localising means may be configured to determine that an animal was located in said zone between said moments in time. This determining may be performed in the control unit (in a case where the control unit is considered as a part of the animal localising means), a separate unit comprising processing means or an additional unit comprising processing means included in the animal localising means. Thereby a set of moments in time during which said animal was located in said zone may be determined and the correct zone label is assigned to the animal location data for said animal for said set of moments in time.

Furthermore, the control unit of the system may be configured to determine that the stress level criterion is fulfilled if the zone-specific stress level exceeds a reference threshold value. The control unit may alternatively be configured to determine that the stress level criterion is fulfilled if the zone-specific stress level repeatedly exceeds a reference threshold value a predetermined number of times and/or if the zone-specific stress level exceeds a reference threshold value during a predetermined time period.

In some cases, it may not be desirable to trigger an action if the zone-specific stress level exceeds a reference threshold value merely a single time. One single increase in stress levels might be due to a non-reoccurring event, such as a honk from a farm vehicle or a worker sneezing. However, if the threshold value is repeatedly exceeded or exceeded for a predetermined time period, there is a higher probability that some sort of permanent, more severe or at least reoccurring problem is present in the concerned zone and it might, thus, be more appropriate to trigger an action.

The threshold value may in turn differ between the plurality of zones of the dairy farm. As an example, a higher threshold value may be used for profitability zones, i.e. zones where the milk (i.e. the revenue) is harvested or zones related to such harvesting of milk, such as a milking zone, the pre-milking zone and zones within the milking zones (representing e.g. milking stalls).

Said reference threshold value may be a predetermined value, e.g. a predetermined value which corresponds to a stress level that should not be exceeded. Optionally or additionally, the threshold value may be based on at least one historic zone-specific stress level, i.e. a zone-specific stress level previously determined. The threshold value may be determined by a set of historic zone-specific stress levels, where e.g. a mean value of these historic zonespecific stress levels is calculated and optionally a margin is added to that mean value. It might be difficult for a person installing the system to know which value corresponds to a normal stress level in a zone as the stress levels may inherently vary between different zones and between different farms. By basing the reference threshold on at least one historic zone-specific stress level, the system can monitor if the determined zone-specific stress levels deviate from previously determined zone-specific stress levels. By this, the user of the system can monitor if any changes at the dairy farm, like new equipment being installed in any of the zones or hiring new personnel, increases the stress levels among the animals. Another option is that the control unit is configured to determine that the stress level criterion is fulfilled if the zone-specific stress level exceeds a previously determined zone-specific stress level by a predetermined amount or exceeds an average of accumulated previously determined stress levels by a predetermined amount. This also facilitates monitoring of deviating stress levels at the dairy farm.

The control unit may be configured to determine the zone-specific stress level for a group of animals comprising a plurality of animals. In such an embodiment of the invention, the control unit is configured to associate the respective response with the corresponding respective animal location data for each of the plurality of animals in the group of animals. The control unit may further be configured to determine a combined response representative for the group of animals by combining the respective responses, which have been associated with the zone for which the zone-specific stress level is being determined, from each of the plurality of animals in the group of animals and determine the zone-specific stress level for the group of animals based on the combined response. The respective responses may be combined by determining an average stress level value of accumulated responses (which have been associated with the zone for which the zone-specific stress level is being determined) registered from the group of animals during a time period. The time period may be e.g. a second, a minute, an hour, a week, a month etc. A zone-specific stress level determined for a group of animals may be beneficial since some animals may exhibit high stress levels due to e.g. illness which is not related to stress induced by external stressors in a zone. A zone-specific stress level based on responses from such an ill animal may be misleading, and an action may be triggered unnecessarily. However, a zone-specific stress level for a group of animals may be more useful when monitoring the stress induced by external stressors in a zone, since deviating responses from e.g. ill cows in the group of animal will have a lesser impact on such determined zonespecific stress levels.

The plurality of animals which provide responses based on which a zone-specific stress level is determined does not necessarily need to be located in the same zone at the same time. Hence, the responses which are accumulated may be registered during a time period and the control unit may be configured to determine the combined response based on responses which have been associated with the concerned zone and which have been registered from the group of animals during said time period. This means that animals in the group of animals may enter and exit said zone independently of other animals in the group and only the responses which are associated with said zone are used to determine the combined response.

The control unit may additionally or alternatively be configured to determine the combined response representative for a group of animals by combining respective responses from each of the plurality of animals of the group of animals, wherein all respective responses are time-stamped with a set of moments in time during which set of moments in time all of the plurality of animals in the group of animals were located in the zone for which the zonespecific stress level is being determined. In other words, the combined response, and subsequently the zone-specific stress level, is in such an embodiment determined for a group of animals which are all located in the same zone during a time period, such as a second, minute or hour etc. Determining a zone-specific stress level for a group of animals which are all located in the same zone at the same time may be beneficial since moments in time where the stress levels among the animals in the group increase are easier to distinguish. In turn, this increases a user’s chance of identifying a potential external stressor in said zone.

Furthermore, the action triggered by the control unit if the stress level criterion is fulfilled may comprise triggering an alarm. This will notify the user that there might be a problem, such as an external stressor, present in the zone for which the stress level criterion has been fulfilled. Alternatively or additionally, the system may comprise a database comprising a representation of the plurality of zones of the dairy farm. The action may in such a case comprise, if the stress level criterion is fulfilled, that the control unit is configured to update the database by saving the moment in time at which the stress level criterion was fulfilled and associate the saved moment in time with the zone for which the stress level criterion was fulfilled in the representation of the plurality of zones. By saving the moment in time at which the zone-specific stress level fulfilled the stress level criterion in a database, the farmer obtains a comprehensive overview of the history of high stress levels at his/her farm. The system may comprise a GUI (Graphical user interface) via which the farmer can get access to the database and saved information therein.

Optionally or additionally, for a system comprising a database comprising a representation of the plurality of zones of the dairy farm, the action may comprise, if the stress level criterion is fulfilled, that the control unit is configured to update the database by labelling the zone for which the stress level criterion has been fulfilled as a stress inducing zone in the representation of the plurality of zones. The control unit may be configured to indicate the zone which has been labelled as a stress inducing zone on a GUI. This solution may function as an alternative to an alarm going off every time the stress level criterion is fulfilled. At today’s modern dairy farms, various alarms go off for several different systems and machines, which can be overwhelming for a farmer. By labelling the zone for which the stress level criterion has been fulfilled as a stress inducing zone in a representation of a plurality of zones, the farmer can check the database via the GUI at any time which suits him/her to see if there is a problem with stress in any of the zones.

According to another aspect the invention, the object is achieved by a method for monitoring at least one animal in a dairy farm comprising a plurality of zones, which method comprises: determining animal location data comprising in which zone of the plurality of zones the at least one animal is located at certain moments in time; registering via at least one animal sensor arrangement at least one respective response from the at least one animal indicative of a level of physical and/or psychological stress and/or discomfort of the at least one animal at certain moments in time; associating the respective response from the at least one animal with the corresponding animal location data for the same at least one animal to determine in which zone the at least one animal was located at the certain moment in time on which the respective response was registered; determining a zone-specific stress level for a zone in which the at least one animal has been located based on at least one respective response associated with said zone; comparing the zone-specific stress level with a stress level criterion; and triggering an action if the zone-specific stress level fulfils a stress level criterion.

Advantages of the method are as initially described in relation to the system. The respective response and animal location data are received and associated, i.e. the zone label comprised in the animal location data is assigned to the corresponding response, with respect to moment in time, i.e. the certain moment in time comprised in the respective responses and animal location data being the the same or substantially the same for corresponding responses and animal location data, as described for the system. All other terms used above should be interpreted as described in relation to the system.

The animal location data may be determined by any of the solutions described in relation to the system. The at least one animal sensor arrangement and the at least one respective response may be any of the alternatives mentioned in relation to the system.

The comparing the zone-specific stress level with a stress level criterion may comprise comparing the zone-specific stress level with a threshold value. The threshold value may be any of the alternatives described in relation to the system. Furthermore, determining whether the stress level criterion is fulfilled may be done according to any of the alternatives described in relation to the system.

The method may comprise determining the zone-specific stress level for a group of animals comprising a plurality of animals by: associating the respective response with the corresponding respective animal location data for each of the plurality of animals in the group of animals; determining a combined response representative for the group of animals by combining all the respective responses from each of the plurality of animals in the group of animals; and determining the zone-specific stress level for the group of animals based on the combined response. Advantages of these aspects of the method are as described for the corresponding features described in relation to the system. The combined response may be determined according to any of the alternatives described in relation to the system.

The action may in the method comprise triggering an alarm. The action may alternatively or additionally comprise to update a database comprising a representation of the plurality of zones of the dairy farm, by: saving the moment in time at which the stress level criterion was fulfilled, and associating the saved moment in time with the representation in the database of the zone for which the stress level criterion has been fulfilled; and/or labelling the representation in the database of the zone for which the stress level criterion has been fulfilled as a stress inducing zone.

Advantages of these aspects of the method are as initially for the corresponding feature described in relation to the system.

BRIEF DESCRIPTION OF DRAWINGS

The invention is now to be explained more closely by means of preferred embodiments, which are disclosed as examples, and with reference to the attached drawings.

Fig. 1 shows a schematic representation of a dairy farm/part of a dairy farm and a zoning thereof.

Fig. 2 shows a schematic representation of another example of a part of a dairy farm and a zoning thereof.

Fig. 3 shows illustrations of various approaches of determining a zone-specific stress level.

Fig. 4 shows embodiments of animal sensor arrangements.

Fig. 5 shows embodiments of animal localising means.

Fig. 6 shows a schematic illustration of a representation of zones of a dairy farm in a coordinate system.

Fig. 7 shows a graph displaying a zone-specific stress level with regard to time and an embodiment of a GUI. Fig. 8 shows a method for monitoring at least one animal in a dairy farm comprising a plurality of zones

DETAILED DESCRIPTION

Fig. 1A schematically illustrates a dairy farm 1 , or a part of a dairy farm 1 , on which a system or method, for monitoring at least one animal 100 in a dairy farm 1 comprising a plurality of zones, according to the invention can be used. The illustrated dairy farm 1 comprises different areas Ai - A?, both indoors and outdoors areas, where animals 100 housed at the dairy farm 1 are located. The animal 100 is in this case a dairy cow, but it is conceived that the animal 100 can be e.g. a buffalo, sheep, goat etc. The area at the top and to the left of the figure is a pre-milking area Ai where the dairy cows are held waiting to be milked. When it is their time to get milked, the dairy cows continue into the milking-area A₂. In the illustrated example, the milking area A₂ comprises milking stalls 11 with milking points 10 via which milk gets extracted from the teats of the dairy cows in manner well-known in the art. These milking stalls 11 may be referred to as sub-areas of the milking area A₂.

After being milked, the dairy cows continue, via a walking alley A3, to a resting area A4 with several sub-areas in the form of resting cubicles 12. From the resting area A4, the dairy cows can go out on pasture on a pasture area Ae or reach a feeding area As to eat. Finally, from the feeding area As, the cows can walk through a second walking alley A? to reach the waiting area Ai once again.

Fig. 1 B shows a zoning of the dairy farm 1 illustrated in fig. 1 A. The different areas of the dairy farm 1 are each represented by a zone Z with a respective unique zone label Z1 - Z7. The sub-areas of the milking area A₂ and the resting area A4, i.e. the milking stalls 11 and resting cubicles 12, are represented by zones Z with zone labels Z₂.i - Z₂.4 and Z4.1 - Z4.7, which are zones within the zones Z₂ and Z4, respectively. It should be noted that the subscript of the areas and the zone labels are not important to the present invention, they are merely one way of denominating different areas and zones.

Fig. 2A schematically illustrates a part of another type of dairy farm 1 where a system or method, for monitoring at least one animal 100 in a dairy farm 1 comprising a plurality of zones, according to the invention can be used. A rotary platform 13 is installed in a milking area A₂ on the dairy farm 1 illustrated in Fig. 2A. Milking on a rotary platform 13 is known in the art and will not be described in detail herein. In short, the animals 100, in this case dairy cows, step onto the rotary platform 13 coming from a pre-milking area Ai. Each dairy cow then stands in a bail 14 on the rotary platform where each bail 14 comprises a milking point 10 via which milk are extracted from the dairy cows. The rotary platform rotates while the cows are being milked and when it has rotated one revolution the dairy cows step of the rotary platform into a walking alley A3 and then continue into an area A4 and then into other areas that follows until it reaches the walking alley A_a and back into the waiting area A1 once again.

Fig. 2A shows a zoning of the dairy farm 1 illustrated in Fig. 2A. The different areas of the dairy farm 1 are each represented by zones Z with a respective unique zone label Z1 - Z_a. The sub-areas of the milking area A₂, i.e. the bails 14 on the rotary platform, are represented by zones Z with zone labels Z2.1 - Z_{2 2}o, which are zones within the zone Z₂.

It should be noted the invention is, of course, not limited for use at dairy farms of the types illustrated in Fig. 1 and Fig. 2. The system according to the invention may be used on any dairy farm 1 regardless of the size, layout, milking equipment installed, etc.

Turning to Fig. 3 which shows various approaches of determining zone-specific stress levels S_z in a system and method for monitoring at least one animal 100 in a dairy farm 1 comprising a plurality of zones, according to the invention. Such zone-specific stress levels S_z may e.g. be determined for zones Z such as those depicted in Fig. 1 B and Fig. 2B. In Fig. 3A, one animal 100, the animal 100 being a dairy cow, is illustrated walking between two zones Z<p and Z_M. Responses R from the dairy cow, indicative of a level of physical and/or psychological stress and/or discomfort of the dairy cow at certain moments in time, are registered by at least one animal sensor arrangement 300, described in more detail below, at a sampling frequency. The responses R are, thus, time stamped with the certain moment in time they were registered. The sampling frequency may be e.g. one response R per second, per two seconds, per minute, etc. For explanatory purposes, the sample frequency of the responses R is in the embodiment illustrated in Fig. 3A set to one response R per every fifth second. The responses R are subsequently received by the control unit 20.

Furthermore, animal location data P for the dairy cow is determined by animal localising means 200, described more in detail below, at a certain frequency. The animal location data P comprises in which zone Z of a dairy farm 1 , in this simplified example one of the zones Z<p or Z_M, the dairy cow was located at certain moments in time, meaning that the animal location data P is time stamped with the certain moments in time on which the dairy cow was located in the respective zone Z. The frequency at which animal location data P is determined is preferably the same as the sampling frequency for the responses R, but another frequency is possible. For explanatory purposes, the frequency in the illustrated example is set to one determination of animal position data P per every fifth second.

In this example, the animal localising means 200 determines the animal location data P via a control unit 20 of the system, meaning that the control unit 20, or parts thereof, is considered a part of the animal localising means 200. Another possible alternative is that the animal location data P is determined by an additional unit 21 comprising processing means, illustrated in dashed lines in Fig. 3A, which is included in the animal localising means 200. In such a case, the control unit 20 would subsequently receive the animal location data P.

It should be noted here that the point in time at which the animal location data P is determined does not necessarily have to be, although it can be, the same moment in time with which the animal location data P is time-stamped regarding in which zone Z the dairy cow was located. The animal localising means 200 may, via the control unit 20 in this case, thus, be configured to determine which certain moments in time the dairy cow was located in certain zones Z at later stage, being later that the determined certain moments in time.

The control unit 20 is configured associate each response R from the dairy cow with corresponding animal location data P for the dairy cow to determine in which zone Z the dairy cow was located at each moment in time on which each response R was registered. The associating of responses R with animal location data P is made with respect to the certain moments in time with which the responses R and the animal location data P, respectively, are time stamped. The associating can be seen as pairing responses R with animal location data P which are time stamped with the same, or substantially the same, moment in time. Substantially the same moment in time in this context means that responses R and animal location data P which are time stamped with moments in time which fall within the same short time interval, such as a second, a couple of seconds, a minute or a couple of minutes, are associated. The configuration of the control unit 20 regarding which responses R and animal location data P to associate may, thus, be dependent on the frequency at which responses R are registered and animal location data P determined. Another way of describing the associating of response R from the dairy cow with corresponding animal location data P is that the zone label comprised in said corresponding animal location data P is assigned to said response R. As mentioned herein, the animal location data P comprises in which zone Z the dairy cow is located at certain moments in time, meaning that the animal location data P will comprise the unique zone label of that zone Z. In the illustrated example in Fig. 3A, four responses R from and four animal location data P for the dairy cow are registered and determined, respectively. As mentioned, the frequency used in this example is one response R and animal location data P per every fifth second, meaning that the sequence illustrated in Fig. 3A lasted for twenty seconds. As illustrated, a response R from the dairy cow R_t=i was registered at the moment in time t=1 , in this case during the first five seconds of the illustrated sequence. Furthermore, determined animal location data P_t=i for the dairy cow is also illustrated, which is time stamped with the moment in time t=1 as well. It should be noted here that the moments in time referred to herein can be short time intervals. In the illustrated example, the moment in time t=1 can cover all responses R and animal location data P which comprises a time stamp which falls within a time interval ranging from 0 to 5 seconds of the illustrated sequence.

The control unit 20 associates the response R_t=i with the animal location data P_t=i due to them being time stamped with the same moment in time t=1. The animal location data P_t=i comprises information that the dairy cow was located in the zone Z<p at the moment in time t=1. The control unit 20 can, thus, determine that the response R_t=i was registered while the dairy cow was located in the zone Z<p. Based on this information and on the indication of the level of physical and/or psychological stress and/or discomfort of the dairy cow comprised in the response R_t=i , the control unit 20 determines a zone-specific stress level S_z<p,t=i for the zone Z<p at the moment in time t=1. In example illustrated in Fig. 3A, zone-specific stress levels S_z are continuously determined in the same manner for the subsequent responses R_t=2

- Rt=₄ and animal location data P_t=2 - Pt=4. The dairy cow leaves the zone Z<p and enters the zone Z_M between the moments in time t=2 and t=3, resulting in that the first two zone-specific stress levels S_z<p,t=i and S_z<p,t=2 appertain to the zone Z<p, while the last two S_ZM,t=i and S_zp,t=2 appertain to the zone Z_M. In other embodiments, the zone-specific stress levels are determined based on a plurality of responses weighed together. In relation to the example illustrated in Fig. 3A, a zone-specific stress level S_z for the zone Z<p may e.g. be based on both the responses R_t=i and R_t=2 weighed together.

Fig. 3B shows an approach of determining a zone-specific stress levels S_z for a zone Z based on a combined response representative for a group of animals comprising a plurality of animals 100. In the illustrated example, the group of animals comprises two dairy cows C1 and C2. The control unit 20 is in this embodiment is further configured to:

- accumulate the responses R which have been associated with the zone Z from the cows C1 and C2 during a time period;

- determine the combined response for the two cows C1 and C2 by calculating an average stress level value based on the accumulated responses R; and

-determine a zone-specific stress level S_z based on the combined response, i.e. based on the calculated average stress level value in this case.

The time period during which the responses R, on which the combined response is based on, have been registered is in the illustrated example from t=1 to t=2.

In Fig. 3B, the dairy cow C1 is outside of the zone Z at the moment in time t=1 while inside the zone Z at the moment in time t=2. The opposite applies for the other dairy cow C2. The control unit 20 associates the respective response R with the corresponding respective animal location data P for each of the two dairy cows C1 and C2 according to the principle described above in relation to Fig. 3A. The control unit 20 then determines that the responses R_t=₂,ci, registered from dairy cow C1 at the moment in time t=2, and R_t=i,c2, registered from dairy cow C2 at the moment in time t=1 , were registered while the dairy cows were located in the zone Z, and the control unit 20 will then determine the combined response for the group of the two cows C1 and C2 by calculating an average stress level value based on these responses R_t=2,ci and R_t=i,c2. The control unit 20 is further configured to determine a zone-specific stress level S_z for the zone Z based on said combined response.

Another embodiment where the control unit 20 is configured to determine a combined response representative for a group of animals is illustrated in Fig. 3C. In this embodiment, the control unit 20 is configured to determine the combined response for a group of animals, in this case a group of dairy cows C1 to Cn, which are all located in the same zone Z at the same time during a time period.

Turning to Fig. 4, which illustrates different animal sensor arrangements 300 for registering respective responses R from animals 100 indicative of a level of physical and/or psychological stress and/or discomfort of the animal 100 at certain moments in time, such as the responses R from the dairy cows referred to in relation to Fig. 3. According to some embodiments, the animal sensor arrangements 300 comprises a tag 220 attached to an animal 100, wherein the tag 220 comprises a rumination sensor 310, a motion sensor 320 and/or a heart rate sensor 330 as described herein. Responses R registered by such sensors are rumination activity, head movements and/or heart rate. Examples of such embodiments are illustrated in Fig. 4A, where tags 220 attached to dairy cows in the ear and around the neck are depicted. Other embodiments of an animal sensor arrangement 300 is shown in Fig. 4B, where cameras 340 are illustrated which are used to register head movements and/or as a rumination sensor 310 to register rumination activity. To avoid repetition, the modes of registering responses R indicative of a level of physical and/or psychological stress and/or discomfort of an animal 100 by the mentioned sensor will not be described in detail here, as it is already described above.

Since stress is negatively correlated to rumination activity, the time spent not ruminating during a time period may be a suitable parameter which is used as a zone-specific stress level S_z in embodiments where a rumination sensor 310 is used to register respective responses R from animals 100. If such embodiments are used for the scenarios depicted in Fig. 3B and 3C, i.e. for groups of animals, the control unit 20 would be configured to determine an average stress level value by dividing the sum of the time spent not ruminating by all of the animals 100 in the group of animals by the number of animals 100 in the group, thus determining the combined response. The zone-specific stress level S_z may in such a case simply be equal to the combined response. In other embodiments using a rumination sensor 310, the respective response R may be whether the animal 100 is ruminating or not, i.e. a YES/NO-type of response. The combined response may in such a case be the total number of animals 100 in the group divided with the number of animals 100 ruminating. The zone-specific stress level S_z may in such a case also be equal to the combined response, as a high number of animals 100 ruminating is indicative of low stress levels.

In Fig. 5, different embodiments of animal localising means 200 are illustrated. A Real Time Location system, abbreviated RTLS, configured to determine an identity reference of animals 100 and a respective position A_rep of the animals 100 at certain moments in time is illustrated in Fig. 5A. The RTLS illustrated, which is known in the art, comprises a tag 220 attached to an animal 100, in this case a dairy cow, such as e.g. by a collar around the neck of the dairy cow as shown in Fig. 5A or attached to the ear as shown in Fig. 5B. The tag 220 emits wireless signals comprising information uniquely identifying the dairy cow, i.e. an identity reference such as a locally or globally unique number, name, and/or code, etc of the dairy cow. It should be noted here that the tag 220 comprised in the RTLS system may be the same tag as the one comprised in the animal sensor arrangements 300 in some embodiments. Thus, the same tag 220 may comprise a sensor to register responses R from the animals 100 and emit wireless signals to determine the respective positions A_rep of the animals 100.

In addition, the RTLS comprises at least three base stations 230a, 230b, 230c which are configured to detect signals emitted by the tag 220. Each base station 230a, 230b, 230c is configured to forward a respective tag message describing the received wireless signal to the control unit 20 of the system.

The control unit 20 is in turn configured to receive the tag messages via a transceiver 260 connected to or comprised in the control unit 20. Based on tag messages received from at least three base stations 230a, 230b, 230c, the control unit 20 is configured to determine the respective positions of the tag 220, e.g. represented by a coordinate in a coordinate system, and thus the positions A_rep of the animal 100, at certain moments in time. The positions A_rep may be determined via e.g. triangulation or trilateration in at least two directions, e.g. two perpendicular directions.

As mentioned above, other alternative processing means than the control unit 20 of the system are possible, such as an additional unit 21 comprising processing means comprised in the animal localising means 200. Thus, in some embodiments, the control unit 20 is replaced by the additional unit 21 with regard to the tasks performed in relation to the RTLS.

In Fig. 6, an approach of determining animal location data P is illustrated according to some embodiments. In the illustrated approach, the animal localising means 200 utilizes a representation Z_rep of a plurality of zones of a dairy farm 1 , stored in a database or another type of data storage, to determine animal location data P by comparing it to positions A_rep of animals 100 at certain moments in time determined by a RTLS.

As illustrated in Fig. 6A, a position A_rep of an animal 100 at a certain moment in time is plotted in a coordinate system 400. In Fig. 6B, a representation Z_rep of a plurality of zones of a dairy farm 1 is plotted in the same coordinate system 400. As can be seen in Fig. 6B, each zone Z covers an area in the coordinate system 400 meaning that each zone Z covers a set, or ranges, of coordinates X and Y in the coordinate system 400. In the illustrated example, the representation Z_rep of the zone Z with the zone label Z₃ covers the set of coordinates X= 10.3 - 15.5, Y= 3.8 - 6.8 and the position A_rep of the animal 100 at a certain moment in time has the coordinate X= 13.5, Y= 4.3. The animal localising means 200 can thus determine, e.g. via the control unit 20 or additional unit 21 , that the animal 100, for which the position A_rep was determined, was located in the zone Z with the zone label Z₃ at the moment in time concerned since the coordinate of its position A_rep is within the set of coordinates covered by the representation Z_rep of said zone Z₃ in the coordinate system 400. The result of this comparison is illustrated in Fig. 6C. As described herein, in other embodiments, which are not illustrated in the figures, the area of a dairy farm 1 is associated with a regular pattern of positions, such as e.g. coordinates in a coordinate system, in which each position in said regular pattern is unambiguously associated with a particular zone Z and the unique zone label of that zone Z. The animal localising means 200 in such embodiments determines, e.g. via the control unit 20 or additional unit 21 , which of the positions in the regular pattern of positions that is closest to a position A_rep of an animal 100 at certain moments in time. The animal localising means 200 subsequently determines, e.g. via the control unit 20 or additional unit 21, that the animal 100 for which the position A_rep has been determined was located in the zone Z which is unambiguously associated with the position in the regular pattern of positions that was determined to be the closest to the position A_rep of said animal 100 at the moment in time concerned.

Another embodiment of animal localising means 200 is depicted in Fig. 5C. In this embodiment, animal identification means 240 are arranged at an entry passage and an exit passage of a zone Z. The animal identification means 240 in the illustrated embodiment comprises ID-readers configured to read ID-tags attached to animals 100 which identifies the animals 100 upon entry through the entry passage and upon exit through the exit passage. When an animal 100 has been identified entering and exiting the zone Z, the animal localising means 200 determines, e.g. via the control unit 20 or additional unit 21, animal location data P for that animal 100 by determining that the animal 100 was located in the zone Z during the time-period between those identification occasions.

Now turning to Fig. 7, where Fig. 7A illustrates a graph where determined zone-specific stress levels S_z are measured along the vertical axis and time t is measured along the horizontal axis. The zone-specific stress S_z levels plotted in the graph are in this example determined for a group of animals comprising a plurality of animals 100, i.e. based on a combined response for the group of animals as previously described. Furthermore, a reference threshold value S_tr is plotted in the graph as a horizontal line. As described herein, this reference threshold value S_tr can be a predetermined value and/or be based on previously determined zone-specific stress levels.

As described herein, the control unit 20 of the system is configured to trigger an action if the zone-specific stress level S_z of a zone Z fulfils a stress level criterion S_c. Fig. 7A illustrates the zone-specific stress level S_z fulfilling a stress level criterion S_c for three different embodiments. In one of said embodiments, illustrated by the left-most vertical dashed line in the graph, the control unit 20 is configured to determine that the stress level criterion S_c is fulfilled if the zone-specific stress level S_z exceeds a reference threshold value Str. I another of the illustrated embodiments, the control unit 20 is configured to determine that the stress level criterion S_c is fulfilled if the zone-specific stress level S_z exceeds the reference threshold value Str during a predetermined time period T_c, depicted by the second left-most vertical dashed line in the graph. Finally, the right-most vertical dashed line in the graph correspond to the third of said embodiments, wherein the control unit 20 is configured to determine that the stress level criterion S_c is fulfilled if the zone-specific stress level S_z exceeds the reference threshold value S_tr repeatedly a predetermined number of times, which predetermined number is three in the illustrated example.

Fig. 7B illustrates a possible outcome when a zone-specific stress level S_z fulfils a stress level criterion S_c according to some embodiments. In said embodiments, the system comprises database comprising a representation Z_rep of a plurality of zones of a dairy farm 1 and the action, when triggered, comprises that the control unit 20 updates said database by labelling the representation Z_rep of the zone Z, for which the stress level criterion S_c has been fulfilled, as a stress inducing zone. The control unit 20 in these embodiments is further configured to indicate the representation Z_rep of the zone Z which has been labelled as a stress inducing zone on a Graphical User Interface (GUI) 500. Such a GUI 500 is depicted in Fig. 7B, wherein the illustrated example is on a smart phone. On the illustrated GUI 500, one zone Z, for which the zone-specific stress level S_z has fulfilled a stress level criterion S_c, is indicated as stress inducing. A user of the system can thereby identify said stress-inducing zone and possibly carry out necessary actions to reduce the stress level.

Finally, Fig. 8 illustrates a method 600 for monitoring at least one animal 100 in a dairy farm 1 comprising a plurality of zones according to the invention. The method comprises: determining 610 animal location data P comprising in which zone Z of the plurality of zones the at least one animal 100 was located at certain moments in time, registering 620 via at least one animal sensor arrangement 300 at least one respective response R from the at least one animal 100 indicative of a level of physical and/or psychological stress and/or discomfort of the at least one animal 100 at certain moments in time, associating 630 at least one respective response R from the at least one animal 100 with the corresponding animal location data P for the same at least one animal 100 to determine in which zone Z said at least one animal 100 was located at the certain moment in time on which said respective response R was registered, comparing 650 the zone-specific stress level S_z with a stress level criterion S_c, and triggering 660 an action if the zone-specific stress level S_z fulfils a stress level criterion S_c.

According to some embodiments, the comparing 650 of the zone-specific stress level S_z with a stress level criterion S_c comprises comparing the zone-specific stress level S_z with a threshold value S_tr.

According to some embodiments the zone-specific stress level S_z is determined for a group of animals comprising a plurality of animals 100 by: associating 630 the respective response R with the corresponding respective animal location data P for each of the plurality of animals 100 in the group of animals, determining 641 a combined response representative for the group of animals 100 by combining all the respective responses R from each of the plurality of animals 100 in the group of animals, and determining 640 the zone-specific stress level S_z for the group of animals based on the combined response.

The action comprises triggering an alarm 661 according to some embodiments.

According to some embodiments, the action comprises to update a database comprising a representation Z_rep of the plurality of zones of the dairy farm 1 , by: saving 662 the moment in time at which the stress level criterion S_c was fulfilled, and associating the saved moment in time with the representation Z_rep in the database of the zone Z for which the stress level criterion S_c has been fulfilled, and/or labelling 663 the representation Z_rep in the database of the zone Z for which stress level criterion S_c has been fulfilled as a stress inducing zone.

The preferred forms of the invention described above are to be used as illustration only and should not be used in a limiting sense to interpret the scope of the present invention. Modifications to the exemplary embodiments, set forth above, could be readily made by those skilled in the art without departing from the spirit of the present invention, as defined by the claims.

Claims

1. A system for monitoring at least one animal (100) in a dairy farm (1) comprising a plurality of zones, the system comprising: animal localising means (200) configured to determine animal location data (P), the animal location data (P) comprising in which zone (Z) of the plurality of zones the at least one animal (100) was located at certain moments in time, at least one animal sensor arrangement (300) for registering at least one respective response (R) from the at least one animal (100) indicative of a level of physical and/or psychological stress and/or discomfort of the at least one animal (100) at certain moments in time, and a control unit (20) configured to: associate at least one respective response (R) from the at least one animal (100) with the corresponding animal location data (P) for the same at least one animal (100) to determine in which zone (Z) said at least one animal (100) was located at the certain moment in time on which said at least one respective response (R) was registered; determine a zone-specific stress level (S_z) for a zone (Z), in which said at least one animal (100) has been located, based on at least one respective response (R) which has been associated with said zone (Z); and trigger an action if the zone-specific stress level (S_z) fulfils a stress level criterion (S_c).

2. The system according to claim 1 , wherein the at least one animal sensor arrangement (300) comprises a rumination sensor (310) and the at least one respective response (R) from the at least one animal (100) comprises a rumination activity of the at least one animal (100).

3. The system according to any of the preceding claims, wherein the at least one animal sensor arrangement (300) comprises a head movement sensor, preferably a motion sensor (320) attached to the at least one animal (100) and/or a camera (340), and the at least one respective response (R) comprises head movements of the at least one animal (100).

4. The system according to any of the preceding claims, wherein the at least one animal sensor arrangement (300) comprises a heart rate sensor (330) and the at least one respective response (R) from the at least one animal (100) comprises a heart rate of the at least one animal (100).

5. The system according to any of the preceding claims, wherein the animal localising means (200) comprises a Real Time Location System (RTLS) configured to determine respective positions (A_rep) of the at least one animal (100) at certain moments in time.

6. The system according to claim 5, wherein the dairy farm (1) is associated with a representation (Z_rep) of the plurality of zones, and wherein the animal localising means (200) is configured to determine in which zone (Z) of the plurality of zones the at least one animal (100) was located at certain moments in time by comparing the representation (Z_rep) of the plurality of zones with the determined respective positions (A_rep) of the at least one animal (100) at certain moments in time.

7. The system according to any of the preceding claims wherein the dairy farm (1) comprises at least one physically separated zone, wherein the at least one physically separated zone is physically separated from other zones of the of the plurality of zones of the dairy farm (1), and wherein the at least one physically separated zone comprises a passage arrangement comprising an entry passage and an exit passage for entry to and exit from the at least one physically separated zone, and wherein the animal localising means (200) comprises animal identification means (240) associated with the respective at least one physically separated zone at which the animal identification means (240) is arranged, the animal identification means (240) being configured to identify the at least one animal (100) upon entry through the entry passage and upon exit through the exit passage, wherein the animal localising means (200) is configured to determine in which zone (Z) of the plurality of zones the at least one animal (100) was located at certain moments in time by registering moments in time on which the identified at least one animal (100) entered and exited the at least one physically separated zone.

8. The system according to any of the preceding claims, wherein the control unit (20) is configured to determine that the stress level criterion (S_c) is fulfilled if the zone-specific stress level (S_z) exceeds a reference threshold value (Str).

9. The system according to any of the claims 1-7, wherein the control unit (20) is configured to determine that the stress level criterion (S_c) is fulfilled if the zone-specific stress level (S_z) repeatedly exceeds a reference threshold value (Str) a predetermined number of times and/or if the zone-specific stress level (S_z) exceeds a reference threshold value (Str) during a predetermined time period (T_c).

10. The system according to any of the claims 8-9, wherein the reference threshold (Str) value is based on at least one historic zone-specific stress level (S_z).

11. The system according to any of the claims 1-7, wherein the control unit (20) is configured to determine that the stress level criterion (S_c) is fulfilled if the zone-specific stress level (S_z) exceeds a previously determined zone-specific stress level (S_z) by a predetermined amount or exceeds an average of accumulated previously determined stress levels (S_z) by a predetermined amount.

12. The system according to any of the claims 8-10, wherein the reference threshold value (Str) differs between the plurality of zones of the dairy farm (1).

13. The system according to any of the preceding claims, wherein the control unit (20) is configured to determine the zone-specific stress level (S_z) for a group of animals comprising a plurality of animals (100) by: associating the respective responses (R) with the corresponding respective animal location data (P) for each of the plurality of animals (100) in the group of animals; determine a combined response representative for the group of animals by combining the respective responses (R) which have been associated with the same zone (Z) from each of the plurality of animals (100) in the group of animals; and determine the zone-specific stress level (S_z) for the group of animals based on the combined response.

14. The system according to claim 13, wherein the control unit (20) is configured to determine the combined response representative for the group of animals by combining respective responses (R) from each of the plurality of animals (100) of the group of animals, wherein all respective responses (R) are time-stamped with a set of moments in time during which set of moments in time all of the plurality of animals (100) in the group of animals were located in the zone (Z) of the dairy farm (1) for which the zone-specific stress level (S_z) is being determined.

15. The system according to any of the claims 13-14, wherein the control unit (20) is configured to combine the respective responses (R) from each of the plurality of animals (100) of the group of animals to determine the combined response by determining an average stress level value of accumulated responses R registered from the group of animals during a time period.

16. The system according to any of the preceding claims, wherein the action comprises to trigger an alarm.

17. The system according to any of the preceding claims, wherein the system comprises a database comprising a representation (Z_rep) of the plurality of zones of the dairy farm (1), and wherein the action comprises that the control unit (20) updates the database by saving the moment in time at which the stress level criterion (S_c) was fulfilled, and associates the saved moment in time with the zone (Z), for which the stress level criterion (S_c) has been fulfilled, in the representation (Z_rep) of the plurality of zones.

18. The system according to any of the preceding claims, wherein the system comprises a database comprising a representation (Z_rep) of the plurality of zones of the dairy farm (1), and wherein the action comprises that the control unit (20) updates the database by labelling the zone (Z), for which the stress level criterion (S_c) has been fulfilled, as a stress inducing zone in the representation (Z_rep) of the plurality of zones.

19. The system according to claim 18, wherein the control unit (20) is configured to indicate the zone (Z) which has been labelled as a stress inducing zone on a Graphical User Interface (500).

20. A method (600) for monitoring at least one animal (100) in a dairy farm (1) comprising a plurality of zones, which method comprises: determining (610) animal location data (P) comprising in which zone (Z) of the plurality of zones the at least one animal (100) was located at certain moments in time; registering (620) via at least one animal sensor arrangement (300) at least one respective response (R) from the at least one animal (100) indicative of a level of physical and/or psychological stress and/or discomfort of the at least one animal (100) at certain moments in time; associating (630) at least one respective response (R) from the at least one animal (100) with the corresponding animal location data (P) for the same at least one animal (100) to determine in which zone (Z) said at least one animal (100) was located at the certain moment in time on which said at least one respective response (R) was registered; determining (640) a zone-specific stress level (S_z) for a zone (Z), in which the at least one animal (100) has been located, based on at least one respective response (R) which has been associated with said zone (Z); comparing (650) the zone-specific stress level (S_z) with a stress level criterion (S_c); and triggering (660) an action if the zone-specific stress level (S_z) fulfils the stress level criterion (S_c).

21. The method according to claim 20, wherein the comparing (650) of the zone-specific stress level (S_z) with a stress level criterion (S_c) comprises comparing the zone-specific stress level (S_z) with a threshold value (Str).

22. The method according to any of claims 20-21, wherein the zone-specific stress level (S_z) is determined for a group of animals comprising a plurality of animals (100) by: associating (630) respective responses (R) with the corresponding respective animal location data (P) for each of the plurality of animals (100) in the group of animals; determining (641) a combined response representative for the group of animals by combining the respective responses (R) which have been associated with the same zone (Z) from each of the plurality of animals (100) in the group of animals; and determining (640) the zone-specific stress level (S_z) for the group of animals based on the combined response.

23. The method according to any of claims 20-22, wherein the action comprises triggering an alarm (661).

24. The method according to any of claims 20-23, wherein the action comprises to update a database comprising a representation (Z_rep) of the plurality of zones of the dairy farm (1), by: saving (662) the moment in time at which the stress level criterion (S_c) was fulfilled, and associating the saved moment with the zone (Z) for which the stress level criterion (S_c) has been fulfilled in the representation (Z_rep) of the plurality of zones; and/or labelling (663) the zone (Z) for which stress level criterion (S_c) has been fulfilled as a stress inducing zone in the representation (Z_rep) of the plurality of zones.