KR20090090489A - Cattle infection managing system through statistical analysis and method thereof - Google Patents

Cattle infection managing system through statistical analysis and method thereof Download PDF

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Publication number
KR20090090489A
KR20090090489A KR1020080015727A KR20080015727A KR20090090489A KR 20090090489 A KR20090090489 A KR 20090090489A KR 1020080015727 A KR1020080015727 A KR 1020080015727A KR 20080015727 A KR20080015727 A KR 20080015727A KR 20090090489 A KR20090090489 A KR 20090090489A
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livestock
health
disease
health status
information
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KR1020080015727A
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Korean (ko)
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임민수
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(주)야긴스텍
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/16—File or folder operations, e.g. details of user interfaces specifically adapted to file systems
    • G06F16/164—File meta data generation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/02—Agriculture; Fishing; Mining
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M3/00—Automatic or semi-automatic exchanges
    • H04M3/42—Systems providing special services or facilities to subscribers
    • H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/12—Messaging; Mailboxes; Announcements
    • H04W4/14—Short messaging services, e.g. short message services [SMS] or unstructured supplementary service data [USSD]

Abstract

Sensor node (100) for collecting the health status measurement information of the individual animals of the livestock breeding in a plurality of barn; Health of the gateway 210 and the sensor node 100 for setting and managing a network for the sensor nodes 100, controlling the operation of each sensor node 100, and receiving and managing health state measurement information of the sensor node 100. A middleware 200 configured as a disease management server 220 to process and manage state measurement information and analyze whether or not it matches the situation model information defined by the user; And a software platform 300 interworking with the middleware 200 to provide an application service for determining whether a livestock disease occurs in the livestock, and the disease management server 220 provides the sensor node 100 with the health state measurement information. A logging unit 222 for classifying and storing the log data in the log database according to the " A filtering unit 223 for processing the health state measurement information into a pattern defined by a user and generating health state metadata; Data for generating average health status (statistics) information for each individual by obtaining average prior information on the body temperature, pulse rate and respiratory rate of the livestock to determine the disease occurrence of the livestock through comparative analysis with the health status measurement information Inference unit 224; And extracting and analyzing the average health status (statistic) information corresponding to the health status metadata, and determining whether or not the disease occurs in the livestock based on the health status metadata. When the same or similar features are found in the livestock farms in the neighboring districts, the infectious disease management system of the livestock is provided through a statistical analysis including a data analysis unit 225 for determining whether an infectious disease has occurred.

Description

Cattle infection managing system through statistical analysis and method

The present invention relates to an infectious disease management system and method of livestock, and more particularly, to analyze the health status of individual cows and pigs, etc., which are raised in livestock farms such as farms, by analyzing data measured through a biosensor and managing them. The present invention relates to a livestock epidemic management system and method through statistical analysis that can effectively prevent and manage the infectious diseases of livestock by judging the occurrence of infectious diseases by region, district and target livestock.

In general, the infectious disease management method of livestock is to check the health status of each cattle or pigs raised in the livestock farm by the farmer or manager to manage the health status measurement information about the development status, body temperature, pulse and respiratory rate of the livestock. The data is recorded in the books and analyzed according to the experience of the farmer or manager, so that the disease of the livestock can be determined and the infectious disease can be determined or offline, and the relevant data can be provided to a livestock expert or veterinarian.

However, the conventional infectious disease management method of a livestock as described above is difficult to manage effectively according to the health status of each individual with a small number of livestock, and provides judgment on the data from the relevant expert or veterinarian through offline. Receiving is not made in real time, there is a problem that takes a lot of time.

In addition, if the disease status of the livestock is not recognized quickly or if the disease is not treated in a timely manner, the transfer of the livestock to neighboring areas, districts and other species as well as other livestock is avoided. Uncountable problems are seriously raised.

Therefore, an object of the present invention is to measure the health status of individual cows or pigs raised in the barn in real time through a biosensor and compare and analyze the health status average (statistics) information regularly updated with each other to suspect a plurality of diseases Infectious disease management system and method of livestock through statistical analysis can be used to effectively prevent and manage the infectious diseases of livestock, if the same or similar health condition occurs in livestock or in the neighboring house. To provide.

According to the present invention, the sensor node 100 for collecting the health status measurement information of the individual animals of the livestock breeding in a plurality of barn; Health of the gateway 210 and the sensor node 100 for setting and managing a network for the sensor nodes 100, controlling the operation of each sensor node 100, and receiving and managing health state measurement information of the sensor node 100. A middleware 200 configured as a disease management server 220 to process and manage state measurement information and analyze whether or not it matches the situation model information defined by the user; And a software platform 300 interworking with the middleware 200 to provide an application service for determining whether a livestock disease occurs in the livestock, and the disease management server 220 provides the sensor node 100 with the health state measurement information. A logging unit 222 for classifying and storing the log data in the log database according to the " A filtering unit 223 for processing the health state measurement information into a pattern defined by a user and generating health state metadata; Generating average health information (statistics) of each individual by obtaining average prior information about the body temperature, pulse rate, and respiratory rate of the livestock to determine the disease occurrence of the livestock through analysis and comparison with the health status measurement information A data inference unit 224; And extracting and analyzing the average health status (statistic) information corresponding to the health status metadata, and determining whether or not the disease occurs in the livestock based on the health status metadata. When the same or similar features are found in the livestock farms in the neighboring districts, the infectious disease management system of the livestock is provided through a statistical analysis including a data analysis unit 225 for determining whether an infectious disease has occurred.

In addition, according to the present invention, the step of generating the health status average (statistics) information for each individual for the body temperature, pulse and respiratory rate of the livestock divided by zone, zone, target animals; Measuring health state measurement information including body temperature, pulse rate and respiratory rate of the individual animals in the breeding house in the barn divided by region, region and region; The health state measurement information is identified, managed by each region, region, or target livestock and processed into predefined health state metadata; Determining health condition average (statistical) information corresponding to the health state metadata, comparing and analyzing each other, and determining whether or not diseases occur in the livestock of the barn based on the health condition; If it is determined in this step that the plurality of individual animals are diseased, the health status metadata of the plurality of individual objects are compared and analyzed, and based on this, the presence or absence of an infectious disease of the domestic animals is determined; And if it is determined in the step that the livestock affected by the infectious disease is provided a method for managing the epidemic disease of the livestock through a statistical analysis comprising the step of notifying the determination information to the barn farmers or managers and infectious disease management headquarters of the livestock.

Therefore, according to the present invention as described above, by measuring in real time the health status measurement information of the livestock is divided by area, area and target livestock and compared with the health status (statistics) information that is updated regularly, As a result of judging the health status of each livestock, if the same or similar health characteristics occur in the livestock of suspected diseases or in the congregation of adjacent areas, it can be considered as an infectious disease, enabling efficient epidemic management of multiple livestock. It can be done.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram schematically showing a system for managing infectious diseases of livestock through statistical analysis according to a preferred embodiment of the present invention.

As shown in Figure 1, the infectious disease management system of livestock through statistical analysis according to a preferred embodiment of the present invention, the sensor node for collecting the health status information of the individual animals of the livestock in large livestock farms ( 100, a gateway 210 and a sensor node 100 for setting and managing a network for the sensor nodes 100, controlling the operation of each sensor node 100, and receiving and managing health state measurement information of the sensor node 100. Process the health status measurement information of the) and analyzes whether or not the consistency with the user-defined situation model information, the middleware 200 consisting of the disease management server 220 and the middleware 200 is connected to the network whether the disease occurrence of the livestock It includes a software platform 300 for providing an application service to determine.

Here, the application service of the software platform 300, by comparing the health status measurement information of the sensor node 100 with the analysis of the disease occurrence of the livestock to determine whether the disease, etc. Obtain average dictionary information on species, gender, age, body temperature, pulse rate, and respiratory rate to database the average health status information for each individual, and allow middleware 200 to measure the health status information and health status average ( Statistical) Comparative information is analyzed between each other to determine whether livestock diseases are occurring, and if the health status measurement information about the suspected livestock is similar, the application of a series of processes is performed to determine the infectious disease and to take prompt action. Include.

The sensor node 100 may be classified by zone, zone, and target livestock, and may be worn or attached to an individual body of a livestock to measure health state measurement information such as body temperature, pulse rate, and respiratory rate of the livestock. Sensor 110, the data communication unit 120 for collecting the health state measurement information of the biosensor 110 and transmits to the gateway 210, the sensor controller 130 for performing a control command for the biosensors 110 ) And a biosensor reader 150 composed of the sensor status unit 140 for monitoring the status information of the biosensors 110.

Here, the biosensor 110 is preferably a kind of electronic tag attached to or inserted into the neck, ear or chest of the livestock in the form of a necklace or earring, etc. and having a unique ID for individual identification. Measures the health status of the livestock in real time, further including a body temperature measuring instrument 111 to measure the pulse of the livestock, and a respiratory rate measuring unit 113 to measure the respiratory rate of the livestock. And, upon request of the sensor control unit 130 provides the health status measurement information of the livestock with a unique ID.

In addition, the biosensor reader 150 also preferably has a unique ID for recognition by region, region, and target livestock, and the gateway 210 when providing the health status measurement information of the corresponding livestock from the biosensor 110. Provide with a unique ID.

Therefore, according to the sensor node 100 as described above, it is possible to measure the effective health state measurement information in real time for the livestock is classified by area, zone and target livestock.

The gateway 210 of the middleware 200 manages data collection between the sensor nodes 100 to be efficiently processed, and the data communication unit 211 and sensor node filter and transmit the information transmitted from the sensor node 100 to the middleware. Status information of the sensor node management unit 212 and the sensor node 100 connected to the gateway 210 to apply control commands such as setting sleep or operation time through scheduling with respect to 100, for example, each sensor node ( Sensor node routing that manages network settings for all sensor nodes 100 connected to the gateway 210 and the sensor node monitor unit 213 for managing and monitoring power remaining, operation status, and connection status of the servers in real time. Part 214 is included.

In addition, the disease management server 220 of the middleware 200, the sensor node for performing the maintenance and management function for the middleware 200 corresponding to each sensor node network by enabling the simultaneous connection of various types of sensor node network The health unit measurement information received from the gateway 210 and the logging unit 222 and the gateway 210 that classify the health state measurement information received from the network unit 210 and store the log state in the log database by the user 210. Filtering unit 223 for generating a health state metadata by processing into a pattern defined by the registration, and registers and manages all possible situation model information, and analyzes the elements suitable for the query requested from the application service of the software platform 300 appropriate Data inference unit 224 for generating a condition and element name, using the data mining technique to log information of the health state metadata In the data analysis unit 225 and the application service, which analyzes the data pattern and analyzes whether or not the user-defined situation model information is consistent with the event model suitable for the application service and the data suitable for the situation model information required by the application service. Protocol module for transmitting a message suitable for the protocol required by the application service of the data transmission unit 226 and the software platform 300 to transmit the event information matching the requested data and the situation model information to the application service unit 227 It includes an application service unit 227 to support.

Referring to the disease management server 220 as described above in more detail.

First, the health status measurement information for each individual animal from the sensor node 100 configured for each zone, region, or target livestock by the application service of the software platform 300 is logged through the gateway 210 through the gateway 210. ), The logging unit 222 classifies and stores the health status measurement information of the livestock by the gateway 210 to identify and manage the corresponding area, the area or the target livestock, and the filtering unit 223 of the livestock Health status measurement information is processed into predefined health status metadata.

Here, the health state metadata is for improving the future utilization of the health state measurement information, and additional information on the health state measurement information, for example, the livestock environment of the livestock at the time of generation of the health state measurement information. Or biological characteristics such as sex, age, vaccination and pregnancy / birth of the livestock.

Meanwhile, the data inference unit 224 analyzes the health status measurement information of the sensor node 100 and analyzes the health status of the livestock to determine the disease occurrence of the livestock. Obtain average (statistical) prior information on age, body temperature, pulse rate, and respiratory rate and database the average health status of each individual.

Here, the health status average (statistical) information, for example, the health status average (statistical) information about the body temperature (pulse or respiratory rate) of the specific livestock is minute, hourly or daily or weekly Or variously classified to correspond to all possible situations for the disease management judgment on a monthly basis and is regularly updated according to the development status of the livestock based on the health status metadata.

The data analysis unit 225 extracts the health state average (statistical) information of the data inference unit 224 corresponding to the health state metadata, compares and analyzes each other, and determines whether a disease occurs in the livestock based on this. If it is judged to have similar characteristics by comparing and analyzing the health status metadata of suspected domestic animals, it is generated as infectious disease judgment reference data for judging infectious diseases, and the other livestock, neighboring districts, districts and target livestock adjacent to the livestock It is determined by statistical analysis whether it is a disease only or a communicable disease that occurred only in the relevant barn by comparing with the standard data of infectious disease judgment in each barn.

For example, when the health status metadata of 'female voice actor 1', 'female voice actor 2' and 'male voice actor 1' in the 'A' area barn indicate body temperature for each minute, the data analyzer 225 ) Is the average of the female voice actor 1, the female voice actor 2, and the male voice actor 1 in the 'A' district barn among the health state averages (statistics) of the data inference unit 224 previously processed. Body temperature can be extracted and compared to each other to determine whether or not the disease occurred in the livestock through judging whether or not.

More specifically, the measured body temperature / pulse / breathing rate of 'female voice actor 1' in the 'A' stall is 40 ° C./75 times / 33 times, respectively, and the corresponding body temperature / pulse per minute is corresponding. If the breathing rate is 37.5 ℃ -39.5 ℃ / 60 times-80 times / 18 times-30 times, respectively, 'female voice actor 1' in the 'A' zone barn is determined to have a problem in body temperature and respiration rate The livestock disease may be suspected.

In addition, the measured body temperature / pulse / respiration of the female voice actor 2 in the 'A' stalls at 41 ℃ / 73 times / 35 times, respectively, and the corresponding body temperature / pulse / respiration by the minute unit, respectively In case of 37.5 ℃ -39.5 ℃ / 60 times-80 times / 18 times-30 times, 'female voice actor 2' in the 'A' zone barn is also considered to have a problem in body temperature and respiratory rate. The disease can be suspected.

In addition, the measured body temperature / pulse / breathing rate of 'male voice actor 1' in the 'A' stall is 43 ℃ / 75 times / 36 times, respectively, and the corresponding body temperature / pulse / breathing rate for each minute In case of 37.5 ℃ -39.5 ℃ / 60 times-80 times / 18 times-30 times, 'male voice actor 1' in the 'A' district stall is also considered to have a problem in body temperature and respiratory rate. The disease can be suspected.

Here, the measured body temperature / pulse / respiration by the minute unit of the livestock raising in the 'A' stalls while maintaining the average temperature / pulse / respiration in a certain section while the average range of the average temperature / pulse / respiration in a certain section If you leave for a certain period of time, you may suspect the disease in the livestock.

In addition, the disease occurrence determination for the livestock is made through a case in which any of the health state metadata corresponding to the body temperature, the respiratory rate and the pulse is out of the error range, or the body temperature and the respiratory rate, the body temperature and the pulse and the respiratory rate. It is preferable that any one of the conditions of the combination of the pulse and the out of the error range or all of the above conditions, such as body temperature, respiratory rate and the intersection condition of the pulse and the like out of the error range.

Therefore, the data analysis unit 225, the 'female voice actor 1', 'in breeding in the' A 'zone barn through the statistical analysis by comparing the health status metadata and the corresponding health status average (statistical) information When female voice actor 2 'and' male voice actor 1 'have a disease, they compare and analyze the health status metadata of the corresponding livestock, and if the health status metadata are similar, they are generated as infectious disease judgment reference data for judging an infectious disease. This is compared with the infectious disease judgment standard data of the 'B' section barn in the same farm, and the infectious disease if the livestock of the 'A' barn is also developed in the adjacent 'B' barn as described above. If not, it is determined that the disease occurred only in the house.

In other words, if the same or similar health status features are found in a plurality of livestock animals suspected of being diseased as a result of the individual health status determination of individual animals, or if the characteristics also occur in livestock farms in adjacent areas, this is determined as an infectious disease. .

On the other hand, the disease management server 220, as determined by the data analysis unit 225 as a result of determining whether the disease occurred by a specific livestock, zone, zone, and target livestock, as determined above, if the livestock is determined to have a disease, Alternatively, the animal may further include an ARS / SMS / MMS unit 228 for notifying ARS / SMS / MMS to the animal husbandry farmer or manager and infectious disease management headquarters of the animal when it is determined that the livestock are infected with an infectious disease. .

In addition, it is preferable to further include on / offline components for analyzing the judgment information by an external expert or a veterinarian and receiving a result corresponding thereto in order to determine the accuracy of the disease and infectious disease occurrence.

Therefore, according to the middleware 200 as described above, the health status measurement information of each individual for the animals reared by zone, zone and target livestock is compared with the corresponding health status average (statistic) information to determine whether or not Through this, it is possible to determine whether the disease is an infectious disease together with the occurrence of disease in the livestock, and can efficiently and quickly accurately.

 Here, the health status average (statistical) information is updated regularly, so that the comparative analysis of the health status measurement information of a specific livestock can be more statistically and accurately.

In addition, if the same or similar health characteristics are found in a plurality of livestock suspected of disease or the livestock of the adjacent area as a result of the individual health status determination of each livestock, it is possible to promptly respond by determining it as an infectious disease It can be done.

Hereinafter, a method for managing infectious diseases of livestock through statistical analysis according to a preferred embodiment of the present invention having the above configuration will be described in more detail.

Figure 2 is a control flow chart showing the infectious disease management method of livestock through a statistical analysis according to a preferred embodiment of the present invention, Figure 3 is a health measured by a biosensor in a livestock epidemic management method through the statistical analysis of FIG. FIG. 4 is a diagram illustrating an example of a comparative analysis graph between status measurement information and corresponding average health status (statistic) information, and FIG. 4 is measured by a biosensor in a method of managing a livestock epidemic through statistical analysis of FIG. 2. Figure 1 is a diagram showing an embodiment of a comparative analysis of epidemic determination through the epidemic determination criteria data.

First, as shown in Figure 2, by the data inference unit 224 of the disease management server 220, the species, sex, age, body temperature, pulse and Health status average (statistical) information for each individual, such as the respiratory rate is database (S100).

Subsequently, health status measurement information such as body temperature, pulse rate and respiratory rate of the livestock is measured by the biosensor 110 attached to the individual for the livestock raised in the barn classified by zone, zone, and target livestock. It is transmitted to the management server 220 (S110).

Subsequently, the health state measurement information is classified by the gateway 210 by the logging unit 222 of the disease management server 220 to identify and manage each region, area or target animal for the livestock of the health state measurement information. Then, the health state measurement information of the livestock is processed by the filtering unit 223 into a predefined health state metadata (S120).

Subsequently, the health state average (statistical) information of the data inference unit 224 corresponding to the health state metadata is extracted by the data analysis unit 225 of the disease management server 220, and the animal is compared and analyzed based on this. It is determined whether the disease occurs (S130).

Here, as shown in FIG. 3, in the step S130, when the health state metadata includes body temperature / pulse / breathing per minute unit of 'female voice actor 1' in the 'A' zone barn, data analysis The unit 225 is the average body temperature / pulse / respiration of the minute unit corresponding to the 'female voice actor 1' of the 'A' zone barn among the health state average (statistical) information information of the data inference unit 224 previously processed Is extracted and compared with the health state metadata to determine whether or not the disease occurrence of the 'female voice actor 1' through the determination of match (error range).

That is, the measured body temperature / pulse / respiratory rate of 'female voice actor 1' in the 'A' stall is 40 ℃ / 75 times / 33 times, respectively, and the corresponding average body temperature / pulse / respiration rate for each minute unit is In case of 37.5 ℃ -39.5 ℃ / 60 times-80 times / 18 times-30 times, 'female voice actor 1' in the 'A' zone barn is judged to have a problem in body temperature and respiratory rate. The disease can be suspected.

In addition, the measured body temperature / pulse / respiration per minute of the 'female voice actor 1' in the 'A' stall, while maintaining the average body temperature / pulse / respiration in a certain section, the average temperature / pulse / respiration in a certain section If you continue to deviate from the average range for a certain period of time, you may suspect the disease in the livestock.

Here, the determination of the occurrence of the disease in step S130 is made through the case in which any one of the health state metadata corresponding to the body temperature, the respiratory rate and the pulse is out of the error range (average range) or the body temperature and the respiratory rate, the body temperature and the pulse And when the combination condition of the respiratory rate and the pulse is out of the error range or the above conditions are all out of the error range such as the body temperature, the repetition condition of the respiratory rate and the pulse, and the like.

Thereafter, it is determined by the data analysis unit 225 that the livestock is diseased at step S130 (S140), and it is determined whether the livestock with the disease is a plurality of individuals bred in the same barn (S150).

If, in the step S140, the disease analysis of the livestock by the disease analysis server 225 of the disease management server 220 determines that the livestock disease is not determined that the disease, the disease induction server of the disease management server 220 The health state average (statistical) information is updated based on the health state metadata by step 224 (S160).

Subsequently, when it is determined in step S150 that the livestock of the plurality of individuals has a disease, the health status metadata of the plurality of individuals having the disease is compared and analyzed by the data analysis unit 225 of the disease management server 220. Through the infectious disease determination reference data is generated (S170).

For example, when 'female voice actor 2' and 'male voice actor 1' are diseased in addition to 'female voice actor 1' in the 'A' barn, the health status metadata of the livestocks is compared with each other. And if the health state metadata are similar, they are generated as infectious disease judgment reference data.

Subsequently, the infectious disease determination reference data is analyzed by the data analysis unit 225 of the disease management server 220 in comparison with the infectious disease determination reference data for the livestock of the livestock according to the neighboring zones, districts and target livestock (S180). .

Thereafter, by the data analyzing unit 225, the infectious disease determination reference data and the infectious disease determination reference data for the livestock of the neighboring barn (by area, region, and target livestock) are similar to each other, and thus the plurality of the relevant barn or the nearby barn If it is determined that the livestock of the individual has an infectious disease (S190), the determination result is notified ARS / SMS / MMS to the barn farmer or manager and the infectious disease management headquarters (S200).

Here, in step S190, as shown in Figure 4, the infectious disease determination reference data of the 'A' zone barn is the infectious disease determination reference data of the 'B' zone barn closest to the 'A' zone barn is compared and analyzed If they are similar, it is determined that an infectious disease has occurred in the 'A' barn and 'B' area barn, otherwise it is determined that a specific disease has occurred in the livestock of the barn.

On the other hand, if it is not determined that the livestock of a plurality of individuals in the step S150 is diseased, or if the livestock of the 'A' district barn is not determined to have an infectious disease in the step S190, the determination information of the steps S140 and S180 ARS / SMS / MMS is notified to the livestock farm owner or manager (S210).

The step S170 may further include analyzing the determination information by an external expert or a veterinarian and receiving a result corresponding to the accuracy of the determination of the occurrence of the infectious disease.

On the other hand, the present invention, if it is determined in step S170 that the livestock of the plurality of individuals have a disease, health status metadata for the plurality of individuals with the disease by the data analysis unit 225 of the disease management server 220 If they are compared and analyzed and the health status metadata are similar, it may be determined that the domestic animals have an infectious disease, and thus the steps S180 and S190 may be omitted.

Therefore, according to the above, the health status measurement information of livestock categorized by zone, zone and target livestock is measured in real time and compared with the regularly updated health status (statistic) information to generate disease of the livestock. The presence or absence can be determined through statistical analysis.

In addition, if the same or similar health status features are found in a plurality of animals suspected of disease as a result of the individual health status determination of each animal, or if the characteristics occur in a congregation in an adjacent area, it is determined as an infectious disease and prompt response is made. You can do that.

In addition, it is possible to promptly protect the epidemic by determining the occurrence of an infectious disease by region, region and target livestock.

In the above-described invention, specific embodiments have been described, but various modifications may be made without departing from the scope of the invention. Thus, the scope of the invention should not be defined by the described embodiments, but should be defined by the equivalents of the claims and claims.

1 is a block diagram schematically showing a system for managing infectious diseases of livestock through statistical analysis according to a preferred embodiment of the present invention;

2 is a control flow chart showing a method for managing infectious diseases of livestock through statistical analysis according to a preferred embodiment of the present invention;

FIG. 3 is a diagram illustrating an embodiment of a comparative analysis graph between health state measurement information measured by a biosensor and corresponding health state average (statistics) information in a method of managing a livestock epidemic through statistical analysis of FIG. 2; FIG. ; And

FIG. 4 is a diagram illustrating an example of a comparative analysis graph of infectious disease determination using infectious disease determination reference data measured by a biosensor in a method for managing infectious diseases of livestock through the statistical analysis of FIG. 2.

Claims (10)

 Sensor node (100) for collecting the health status measurement information of the individual animals of the livestock breeding in a plurality of barn; Health of the gateway 210 and the sensor node 100 for setting and managing a network for the sensor nodes 100, controlling the operation of each sensor node 100, and receiving and managing health state measurement information of the sensor node 100. A middleware 200 configured as a disease management server 220 to process and manage state measurement information and analyze whether or not it matches the situation model information defined by the user; And It includes a software platform 300 that provides an application service for determining whether the disease occurs in the livestock by interworking with the middleware 200, the network, Disease management server 220, A logging unit 222 for classifying the health state measurement information for each sensor node 100 or gateway 210 and storing the health state measurement information in a log database; A filtering unit 223 for processing the health state measurement information into a pattern defined by a user and generating health state metadata; Data for generating average health status (statistics) information for each individual by obtaining average prior information on the body temperature, pulse rate and respiratory rate of the livestock to determine the disease occurrence of the livestock through comparative analysis with the health status measurement information Inference unit 224; And The health status averages (statistics) corresponding to the health status metadata are extracted and analyzed. The health status metadata of the domestic animals suspected of disease is determined by comparing and analyzing each other. Or an infectious disease management system of a livestock through a statistical analysis, characterized in that it comprises a data analysis unit (225) to determine whether or not an infectious disease occurs based on this or when the characteristics are found to be the same or similar to livestock livestock of the adjacent area. The method of claim 1, wherein the sensor node 100 is divided into zones, zones, and target livestock, and is worn or attached to a body of a livestock to measure the state of health including body temperature, pulse rate, and respiration rate of the livestock. Statistical analysis, characterized in that it comprises a biosensor 110 for measuring information, and a biosensor reader 150 for collecting and controlling the health state measurement information of the biosensor 110 to transmit to the gateway 210 Livestock epidemic management system. The biosensor 110 according to claim 2, wherein the biosensor 110 is attached to or inserted into a corresponding site of the livestock, has a unique ID for individual identification, measures the body temperature, pulse and respiratory rate of the livestock, and measures the biosensor reader 150. Infectious disease management system of livestock through statistical analysis, characterized in that the electronic tag provided to). According to claim 1, wherein the average health status (statistics) information on the body temperature / pulse / respiration of the individual of the livestock infectious disease management judgment by the minute, hour or date or weekly or monthly basis Infectious disease management system of livestock through statistical analysis, characterized in that it is variously classified to correspond to all possible situations for the development and regularly updated according to the development status of the livestock based on the health state metadata. The method of claim 1, wherein the disease management server 220, if it is determined that the livestock disease is diseased through the statistical analysis, characterized in that notified ARS / SMS / MMS to the cattle farm owner or manager of the livestock livestock Livestock Epidemic Management System. Generating health status averages (statistics) for each individual on the body temperature, pulse rate, and respiratory rate of the livestock classified by zone, zone, and target livestock; Measuring health state measurement information including body temperature, pulse rate and respiratory rate of the individual animals in the breeding house in the barn divided by region, region and region; The health state measurement information is identified, managed by each region, region, or target livestock and processed into predefined health state metadata; Determining health condition average (statistical) information corresponding to the health state metadata, comparing and analyzing each other, and determining whether or not diseases occur in the livestock of the barn based on the health condition; If it is determined in the step that the cattle of the plurality of individuals are ill, the health status metadata of the plurality of individuals is compared and analyzed and based on the determination of the presence of infectious diseases of the cattle; And If it is determined in the step that the livestock are infected with the infectious disease, the determination information comprises a step of notifying the livestock farm owner or manager and the infectious disease management headquarters of the livestock epidemic disease management method characterized in that it comprises a statistical analysis. The method according to claim 6, further comprising the step of generating infectious disease determination reference data based on a comparative analysis of health status metadata of the plurality of individuals affected by the disease when determining whether the corresponding livestock epidemic has occurred. How to control livestock epidemic through statistical analysis. The method according to claim 7, wherein the infectious disease judgment reference data is compared with the infectious disease judgment reference data for the livestock of the livestock of each district, district and target livestock to determine whether or not the infectious disease of the relevant livestock is judged when they are similar to each other. Infectious disease management method of a livestock using a bioassay, characterized in that. The method of claim 6, wherein if the livestock is not determined to have a disease, the average health status (statistical) information is updated based on the health status metadata. 10. The method of claim 9, wherein the disease occurrence determination of the livestock is made through a case in which any one of the health state metadata corresponding to body temperature, respiratory rate and pulse rate is out of an error range, or the temperature and respiratory rate, body temperature and pulse rate, and the like. Livestock through a statistical analysis, characterized in that any one of the respiratory rate and pulse rate combination condition is out of the error range or the body temperature, respiratory rate and pulse rate intersection condition all of the above conditions are out of the error range How to control epidemics.
KR1020080015727A 2008-02-21 2008-02-21 Cattle infection managing system through statistical analysis and method thereof KR20090090489A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014015215A3 (en) * 2012-07-19 2014-03-06 Cepheid Remote monitoring of medical devices
CN110574708A (en) * 2018-06-08 2019-12-17 刘丹 Plant disease control management system and management device and inspection robot applied to same
KR20200105558A (en) * 2019-02-28 2020-09-08 주식회사 에스티엔 A Computer Vision for the Prediction System of Livestock Diseases and Their Methods

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014015215A3 (en) * 2012-07-19 2014-03-06 Cepheid Remote monitoring of medical devices
CN110574708A (en) * 2018-06-08 2019-12-17 刘丹 Plant disease control management system and management device and inspection robot applied to same
KR20200105558A (en) * 2019-02-28 2020-09-08 주식회사 에스티엔 A Computer Vision for the Prediction System of Livestock Diseases and Their Methods

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