Health condition monitoring device, health condition monitoring method, and program

Abstract

Provided are a health state ascertaining device, etc., which enable certification that an animal such as livestock has lived healthily in mind and body throughout life, and which contribute to conferring food safety security and peace of mind to consumers. Specifically, provided is a health state ascertaining device including: a behavior data acquisition unit for acquiring behavior data which indicates the behavior of an animal and is acquired by monitoring or sensing the animal; a behavior data storage unit for storing the behavior data; and a health state inference unit for inferring the health state of the animal by using the behavior data.

Description

[Technical Field]

[0001] [Statement about related applications] The present invention is based on a claim of priority to Japanese Patent Application No. 2021-205564 (filed December 17, 2021), the entire contents of which are incorporated herein by reference. The present invention relates to a health condition monitoring device, a health condition monitoring method, and a program. [Background technology]

[0002] In recent years, there has been a growing need to consider how to ensure that not only humans but also livestock and other animals can live comfortably. The concept of "animal welfare" is defined by the international organization OIE (International Organisation for Animal Health) as "the physical and mental state of animals in relation to the environment surrounding their lives and deaths," and each country has created guidelines regarding animal welfare, particularly in the livestock industry.

[0003] Even today, for example, beef cattle are individually identified and their sex, breed, and place of rearing from birth to slaughter and death are recorded, and meat can be traced using individual identification numbers, ensuring food safety and security.However, from the perspective of animal welfare, it is necessary to prove that livestock animals have been raised in a healthy manner both physically and mentally, so new information is needed, such as how livestock animals were raised and whether they were living a healthy life.

[0004] Patent Document 1 discloses the following grazing livestock monitoring system. In this system, sensors are used to collect data on the location, number of steps, and speed of grazing livestock, as well as vital data such as body temperature, pulse rate, respiration, and blood pressure, and store this data in a memory area. Based on this behavior and biological data, AI is used to analyze the psychological state of the grazing livestock. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2019-208470 Summary of the Invention [Problem to be solved by the invention]

[0006] The disclosures of the above prior art documents are incorporated herein by reference. The following analysis has been carried out by the present inventors.

[0007] However, the main purpose of the above-disclosed invention is to monitor the current physical and psychological state of livestock, and it does not comprehensively collect, analyze, and accumulate the trajectory of the mental and physical health of livestock over their lifetimes from the perspective of animal welfare.

[0008] The present invention aims to provide a health status monitoring device, a health status monitoring method, and a program that enable proof that livestock and other animals have lived healthy lives both physically and mentally throughout their lives, and that contribute to ensuring food safety and giving consumers a sense of security. [Means for solving the problem]

[0009] According to a first aspect of the present invention and disclosure, there is provided a health status assessment device having a behavioral data acquisition unit that acquires behavioral data indicating the behavior of an animal obtained by performing at least one of monitoring or sensing on the animal, a behavioral data storage unit that accumulates the behavioral data, and a health status estimation unit that estimates the health status of the animal using the behavioral data.

[0010] According to a second aspect of the present invention and disclosure, there is provided a health status assessment method comprising the steps of acquiring behavioral data indicating the behavior of an animal obtained by performing at least one of monitoring or sensing on the animal, storing the behavioral data in a memory area for accumulation, and estimating the health status of the animal using the behavioral data.

[0011] According to a third aspect of the present invention and disclosure, there is provided a program for causing a computer to execute the following processes: acquiring behavioral data indicating the behavior of an animal obtained by performing at least one of monitoring or sensing on the animal; storing the behavioral data in a memory area for accumulation; and estimating the health condition of the animal using the behavioral data. [Effects of the Invention]

[0012] According to each aspect of the present invention and disclosure, a health status monitoring device, a health status monitoring method, and a program are provided that enable proof that livestock and other animals have lived healthy lives both physically and mentally throughout their lives, and that contribute to ensuring food safety and giving consumers a sense of security. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a block diagram showing an example of the configuration of a health condition determination device according to an embodiment; [Figure 2] 1 is a block diagram showing an example of the configuration of a health condition determination device according to a first embodiment. [Figure 3] FIG. 2 is a conceptual diagram showing an overview of the processing of the health condition determination device according to the first embodiment. [Figure 4] 4 is a flowchart showing an example of the operation of the health condition determining device according to the first embodiment. [Figure 5] 1 is a schematic diagram showing the hardware configuration of a health condition determination device according to a first embodiment. [Figure 6]FIG. 10 is a block diagram showing an example of the configuration of a health condition determining device according to a second embodiment. [Figure 7] FIG. 10 is a schematic diagram showing an overview of the processing of the health condition determination device according to the second embodiment. [Figure 8] 10 is a flowchart showing an example of the operation of the health condition determining device according to the second embodiment. [Figure 9] FIG. 10 is a block diagram showing an example of the configuration of a health condition determining device according to a third embodiment. [Figure 10] FIG. 11 is a schematic diagram showing an overview of the processing of the health condition determining device according to the third embodiment. [Figure 11] 10 is a flowchart showing an example of the operation of the health condition determining device according to the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0014] First, an overview of one embodiment will be described. Note that the reference numerals in the drawings attached to each element in this overview are added for convenience as an example to facilitate understanding, and the description of this overview is not intended to be limiting in any way. Furthermore, the connection lines between blocks in each figure include both bidirectional and unidirectional. Unidirectional arrows are used to schematically indicate the flow of the main signal (data) and do not exclude bidirectionality. Furthermore, although not explicitly shown in the circuit diagrams, block diagrams, internal configuration diagrams, connection diagrams, etc. shown in this disclosure, input ports and output ports exist at the input and output ends of each connection line. The same applies to input / output interfaces.

[0015] 1 is a block diagram showing an example of the configuration of a health condition determination device according to an embodiment. As shown in the figure, a health condition determination device 10 according to an embodiment includes a behavioral data acquisition unit 11, a behavioral data storage unit 12, and a health condition estimation unit 13.

[0016] The behavioral data acquisition unit 11 acquires behavioral data indicating the behavior of animals by performing at least one of monitoring and sensing on the animals. "Animals" include livestock (dairy cattle, beef cattle, pigs, broilers, sheep, horses, etc.). "Monitoring" refers to surveillance, mainly using cameras, while "sensing" refers to measuring certain physical quantities, mainly using sensors. Either "monitoring" or "sensing," or a combination of both, can be used to identify individual animals and trace their condition. Furthermore, any type of camera or sensor, whether contactless or contact, can be used, and any method can be adopted, as long as it does not violate the ethical standards of animal welfare.

[0017] The "behavioral data" may be obtained by acquiring "physical movements" and "conditions" such as biometric information exhibited by the animal. Furthermore, this behavioral data may be acquired after individual identification and may be traceable. The acquired behavioral data is sent to the behavioral data storage unit 12 and health condition estimation unit 13, which will be described later.

[0018] The behavioral data acquisition unit 11 may be realized as a separate device geographically separated from the health condition monitoring device, and the two may be connected via a communication network.

[0019] The behavioral data storage unit 12 stores the behavioral data acquired by the behavioral data acquisition unit 11. "Storage" means saving behavioral data from the present to the past in a storage area. For example, it is possible to store all behavioral data, such as location information from the moment of birth to the present, body temperature, and distance traveled per day. The behavioral data stored here includes, in addition to primary information, which is simply location information recorded over time, secondary information such as distance traveled, which is derived by calculation from the time and location information, etc.

[0020] The health condition estimation unit 13 estimates the health condition of the animal using the behavioral data. "Health condition" refers to the external (mainly physical) and internal (mainly mental) state of the animal, derived from the "behavioral data" according to predetermined procedures and rules. For example, if the behavioral data shows that the animal remains in the same position for a predetermined period of time or longer, it can be estimated that the animal is sleeping, and the time spent there can be estimated as sleeping time. In addition, the obesity level can be estimated from the behavioral data, such as the animal's weight and body fat percentage, and the amount of food intake. Furthermore, the animal's physical condition can be estimated by detecting external injuries or measuring body temperature, for example, using a camera, and comparing these data with past trends to estimate the animal's level of poor health.

[0021] Based on the above behavioral data or estimated health status, it is also possible to estimate an animal's internal state, such as stress level. For example, if an animal has been sleeping less than average over the past two days and has been consuming less food, and the camera repeatedly recognizes a specific gesture that is not normally displayed, it can be assumed that the animal is experiencing stress for some reason. In this way, by linking health status with behavioral data, it is possible to estimate an animal's mental state, such as stress.

[0022] Specific embodiments will be described in more detail below with reference to the drawings. Note that the same components in each embodiment are denoted by the same reference numerals, and the description thereof will be omitted.

[0023] [First embodiment] The first embodiment will be described in more detail with reference to the drawings. Fig. 2 is a block diagram showing an example of the configuration of a health condition determination device 10 according to the first embodiment.

[0024] The health condition determination device 10 of this embodiment has the following configuration. That is, as shown in Fig. 2, the health condition determination device 10 according to the first embodiment has a behavioral data acquisition unit 11, a behavioral data storage unit 12, a health condition estimation unit 13, and a health condition diagnosis unit 14. The difference in configuration between the health condition determination device 10 of this embodiment and the above embodiment is that it newly includes the health condition diagnosis unit 14.

[0025] The health condition diagnosis unit 14 diagnoses the health condition of the animal based on the health condition. Here, "diagnosis" refers to evaluating the health condition estimated by the health condition estimation unit 13 in accordance with predetermined standards and rules, and providing necessary measures (treatment, medication, etc.). Specifically, diagnosis is made by comparing the past data of an individual animal, or by comparing the data of other individuals at the same date and time.

[0026] 3 is a conceptual diagram showing an overview of the processing of the health condition determination device 10 in the first embodiment. As shown in this diagram, the health condition determination device 10 of this embodiment performs processing in the order of behavioral data acquisition unit 11, behavioral data storage unit 12, health condition estimation unit 13, and health condition diagnosis unit 14.

[0027] The behavioral data acquisition unit 11 acquires behavioral data using various devices. For example, it may be configured with a camera installed in the breeding area, a thermography camera that measures body temperature, a 3D sensor that can recognize gestures, a weight sensor that measures weight and remaining amount of food, an acceleration sensor that recognizes movement, etc. Also, a configuration may be adopted in which individual identification is performed by combining a 3D sensor and a camera.

[0028] This acquired behavioral data is stored in the behavioral data storage unit 12. When storing data, each item is stored in chronological order for each individual. As shown in the diagram, for example, data captured by a camera, movement time measured with an acceleration sensor, body temperature acquired with a thermographic camera, and remaining food amount measured with a weight sensor are stored. These data are just examples, and all data that can be acquired as behavioral data is stored in this unit. From the perspective of animal welfare, this data is stored for each individual throughout its lifetime.

[0029] The health condition estimation unit 13 estimates (primary analysis) the health condition using the behavioral data accumulated in the behavioral data accumulation unit 12. For example, it performs processes such as estimating sleep time using photographic data taken at a predetermined timing and movement time, estimating the presence or absence of injuries by subjecting the photographic data to image recognition, and estimating food intake from the amount of remaining food. In this way, the health condition estimation unit 13 combines the data accumulated in the behavioral data accumulation unit 12 and calculates and estimates health information from static data. Since the calculation is performed according to a predetermined rule, the health condition grasping device 10 of this embodiment may have a health condition estimation rule storage unit (not shown) that stores health condition estimation rules.

[0030] The health condition diagnosis unit 14 performs a diagnosis (secondary analysis) using the estimated health condition as described above. As shown in this figure, livestock a has a stable sleep schedule, no external injuries, and its food intake remains within a predetermined range, so it is diagnosed as having no problems. Livestock b has been found to have an injury, and the size of the injury has increased from "small" to "medium" over time. As a result, it is assessed that its condition is worsening due to the injury. In response to this assessment result, necessary measures such as "immediate treatment" are provided as the diagnosis result. Similarly, livestock c is assessed as having a tendency to eat more than other individuals, so necessary measures such as reducing its food intake are provided.

[0031] The above-described process of "evaluation" → "proposal" may be performed using rule-based artificial intelligence. That is, the system may have a health condition evaluation rule storage unit (not shown) and a proposal rule storage unit (not shown). These stored rules are written declaratively, and inference may be performed using the rules. For example, a rule describing knowledge about mastitis in dairy cows may be used to perform inference using declarative rules such as "If fever (increased body temperature), decreased appetite (reduced food intake), decreased milk production (small weight loss before and after milking), and udder swelling (measured by image recognition) are observed, there is a high possibility of mastitis (evaluation rule)" and "If mastitis is present, administration of antibiotics is effective (proposal rule)," and the result may be a diagnosis of "mastitis, and antibiotics should be administered."

[0032] Furthermore, the health condition diagnosis unit 14 may calculate a health index value, which is an index value indicating the health level of the animal, based on the health condition. The index value may be calculated using a predetermined evaluation function. Alternatively, the health condition diagnosis unit 14 may be configured to calculate a desired health condition by performing optimization using the evaluation function and feed it back.

[0033] [Explanation of operation] An example of the operation of the health condition determination device 10 of this embodiment will be described with reference to Fig. 4. Fig. 4 is a flowchart showing an example of the operation of the health condition determination device 10 according to the first embodiment.

[0034] When the device starts operation, it acquires behavioral data (step S41). The acquired behavioral data is accumulated (stored) (step S42). Next, the acquired or accumulated behavioral data is used to estimate the health condition (step S43). After that, the health condition is diagnosed based on the estimated health condition (step S44).

[0035] [Hardware configuration] Health condition determination device 10 of this embodiment can be configured by an information processing device (computer) and has the configuration exemplified in Fig. 5. For example, health condition determination device 10 includes a CPU (Central Processing Unit) 51, memory 52, input / output interface 53, and a NIC (Network Interface Card) 54 as a communication means, which are interconnected by an internal bus 55.

[0036] However, the configuration shown in Figure 5 is not intended to limit the hardware configuration of health condition monitoring device 10. Health condition monitoring device 10 may include hardware not shown, and may not include input / output interface 53 as necessary. Furthermore, the number of CPUs and other components included in health condition monitoring device 10 is not intended to be limited to the example shown in Figure 5; for example, health condition monitoring device 10 may include multiple CPUs.

[0037] The memory 52 is a RAM (Random Access Memory), a ROM (Read Only Memory), or an auxiliary storage device (such as a hard disk).

[0038] The input / output interface 53 is a means for interfacing with a display device or input device (not shown). The display device is, for example, a liquid crystal display. The input device is, for example, a device that accepts user operations, such as a keyboard or mouse, or a monitoring or sensing device, such as a camera, 3D sensor, or weight sensor.

[0039] The functions of the health condition determination device 10 are realized by a group of programs (processing modules) stored in the memory 52, such as a behavioral data acquisition program, a health condition estimation program, and a health condition diagnosis program, and a group of data including the accumulated behavioral data. The processing modules are realized, for example, by the CPU 51 executing each program stored in the memory 52. ​​The programs can be downloaded via a network or updated using a storage medium storing the programs. Furthermore, the processing modules may be realized by a semiconductor chip. That is, it is sufficient if there is some means for executing the functions performed by the processing modules using some kind of hardware and / or software.

[0040] [Hardware operation] When the health condition determination device 10 starts operating, a behavioral data acquisition program is called from the memory 52 and executed by the CPU 51. The program acquires images at predetermined timings using a camera, which is an input device. The program also acquires acceleration data and the like in response to interrupts from an acceleration sensor, which is also an input device. At this time, if the individual identification program is executed by the CPU 51, the acquired behavioral data can be associated with the identified individual.

[0041] The behavioral data acquisition program stores and accumulates the acquired behavioral data in memory 52. ​​Next, the health condition estimation program is called from memory 52 and executed by CPU 51. This program reads the accumulated behavioral data from memory 52, and generates health condition data by combining one or more behavioral data to make an estimate, and stores the data in memory 52.

[0042] Next, the health condition diagnosis program is called from memory 52 and executed by CPU 51. This program reads the health condition data stored in memory 52, performs diagnosis (inference) according to a predetermined diagnostic rule, and outputs the diagnosis result. The predetermined diagnostic rule may be stored in memory 52 as diagnostic rule data.

[0043] [Effect description] The health condition determination device according to the first embodiment can acquire and store behavioral data of animals and estimate their health conditions. It can also perform diagnoses according to their health conditions. This allows the physical and mental health conditions of animals to be determined and possible responses (treatment, etc.) to be known.

[0044] [Second embodiment] In the second embodiment, a health condition determination device capable of acquiring behavioral data of a plurality of animals belonging to the same group and extracting behaviors and individuals in a particular health condition by analyzing the behavioral data will be described.

[0045] Health condition determination device 10 of this embodiment has the following configuration. That is, as shown in Fig. 6, health condition determination device 10 according to the second embodiment has behavioral data acquisition unit 11, behavioral data storage unit 12, health condition estimation unit 13, group detection unit 16, and specific individual extraction unit 15. The difference in configuration between health condition determination device 10 of this embodiment and the above-described embodiment is that it newly includes group detection unit 16 and specific individual extraction unit 15.

[0046] The behavioral data acquisition unit 11 of the health condition determination device 10 of this embodiment acquires behavioral data of multiple animals. The behavioral data storage unit 12 stores the acquired multiple pieces of behavioral data. The health condition estimation unit 13 uses the stored multiple pieces of behavioral data to estimate the health conditions of the multiple animals. The behavioral data acquisition unit 11 may acquire behavioral data of multiple animals belonging to the same group.

[0047] The herd detection unit 16 detects herds of animals. A "herd" refers to a state in which animals are gathered together. A herd unit may refer to, for example, all the animals in a certain barn, or to a group of animals in which the animals voluntarily gather and continuously act together. "Detecting a herd" means identifying the individual animals belonging to the herd. Specifically, for example, the physical range of the herd is specified using a camera or sensor, and the individual animals belonging to the herd are identified by identifying the animals located within that specified range.

[0048] The specific individual extraction unit 15 uses the behavioral data of multiple animals to extract individual animals in a specific state from the multiple animals. A "specific state" refers to, for example, a state in which the animal exhibits behavior that deviates from the collective behavior of a group such as a flock. To grasp this state, for example, the movement speed, gesture types, and frequency of the flock are measured and statistically distributed, and an individual with large fluctuations is determined to be in a specific state. Note that "deviation" includes not only a state in which abnormal behavior is exhibited due to a deterioration in health, but also behavior that occurs even when the animal is in good health.

[0049] FIG. 7 is a schematic diagram showing an overview of the processing of the health condition determination device 10 in this embodiment. First, the group detection unit 16 detects a group. Here, as an example, the group is detected by image recognition using video captured by a camera. Although not shown, processing for identifying individuals using RFID (Radio Frequency Identifier) ​​tags or the like may also be performed. Next, the behavioral data acquisition unit 11 acquires behavioral data of multiple animals belonging to the group. At this time, in addition to the behavioral data of each of the multiple animals (e.g., gesture detection using a 3D sensor), the movement of the group as a whole (movement speed, etc.) is acquired. Next, the behavioral data storage unit stores this acquired data in chronological order.

[0050] The specific individual extraction unit 15 analyzes the accumulated behavioral data and extracts individuals in specific states according to predetermined rules. For example, it analyzes the dispersion and density of individuals within a herd over time, determining whether any individuals are isolated and tallying up the number of contacts between individuals. Specifically, a camera recognizes the position of each individual and detects deviations in the individual's position within the herd, thereby measuring the dispersion and density of individuals within the herd. This is then combined with the individual's behavioral data (such as the individual's movement speed) to detect individuals exhibiting specific behavior. For example, the area around individual a, shown with diagonal lines in Figure 7, is assumed to have a consistently high density of individuals, resulting in frequent contact with other livestock. It is also assumed that the individual's movement speed is faster than that of other individuals. Based on this behavioral data, the shaded individual is suspected of exhibiting abnormal behavior due to stress and is extracted as a specific individual.

[0051] On the other hand, individuals b and c, indicated by dotted hatching, are densely packed, but because they spend a long time in the same place, they are judged to be grooming themselves and are extracted as individuals in good physical and mental health. In this way, the health status monitoring device 10 of this embodiment can extract not only individuals whose physical and mental health has deteriorated and become abnormal as a specific condition, but also individuals in good health. By analyzing the growth environment of individuals in good health and providing feedback to the growth environments of other individuals, improvements can be made.

[0052] Although not shown, the health condition monitoring device 10 of this embodiment may have a specific individual extraction rule storage unit that stores extraction rules for the above-mentioned extraction. For example, the rule used to extract the above individual a may be a rule such as "the stress level of livestock is high when the density of individuals within the herd is relatively high for a predetermined period of time and the movement speed of the individual reaches or exceeds a predetermined speed" and a rule such as "the density of individuals is high when the number of contacts between individuals exceeds a predetermined number within a predetermined period of time," combined with behavioral data acquired by the behavioral data acquisition unit 11, such as the frequency of contact between individual a and other individuals within a predetermined period of time and the movement speed of individual a within a predetermined period of time, to determine by inference whether the target individual is in a state of high stress level and whether the behavior of individual a corresponds to a specific state.

[0053] Furthermore, if the health condition determination device 10 of this embodiment is configured to include the health condition diagnosis unit 14, the diagnosis result for an individual obtained by the health condition diagnosis unit 14 in the first embodiment may be linked to the extraction result of a specific individual for that individual to perform diagnosis. For example, suppose that the health condition diagnosis result for individual a indicates that the individual is in good health. However, the specific individual extraction unit 15 determines that the individual is in an abnormal state and extracts the individual. Based on these results, the device may be configured to output a diagnosis result indicating that the individual is in a healthy state, but is in an abnormal state due to stress within the group, and that preventative measures such as keeping the individual away from other individuals as much as possible should be taken.

[0054] [Explanation of operation] An example of the operation of the health condition determination device 10 of this embodiment will be described with reference to FIG. 8. FIG. 8 is a flowchart showing an example of the operation of the health condition determination device 10 according to the second embodiment. As shown in this figure, when the health condition determination device 10 of this embodiment starts processing, it first detects a flock (step S81). Next, it acquires behavioral data of multiple animals (step S82). The acquired behavioral data is stored and accumulated in a memory area (step S83). The accumulated behavioral data is used to extract specific individuals (step S84).

[0055] [Hardware configuration] The health condition determination device 10 of this embodiment can be configured by an information processing device (computer), and has the configuration exemplified in FIG. 5, similar to the first embodiment.

[0056] The functions of the health status monitoring device 10 of this embodiment are realized by a group of programs (processing modules) stored in memory 52, such as a behavioral data acquisition program, a herd detection program, a specific individual extraction program, etc., and a group of data including accumulated behavioral data.

[0057] [Hardware operation] When the health condition determination device 10 starts operating, a behavioral data acquisition program is called from the memory 52 and executed by the CPU 51. The program acquires video at predetermined times using a camera, which is an input device. The acquired video data is stored and accumulated in the memory 52 as behavioral data. Next, a herd detection program is called from the memory 52 and executed by the CPU 51. The program recognizes the acquired video data and determines the range of the herd. Once the range of the herd has been determined, individuals within the herd are identified using a 3D sensor, RFID tags, the acquired video data, etc.

[0058] Next, the specific individual extraction program is called from memory 52 and executed by CPU 51. This program acquires data such as the positions and movements of individuals belonging to the same herd from video data or from acceleration sensors attached to the animals. The program analyzes the acquired individual positions, movements, etc. For example, it executes processing such as outputting to a display device or the like that an individual whose movement amount exceeds a predetermined value relative to the movement of the entire herd is in an abnormal state. Furthermore, in the health condition determination device 10 of embodiment 1, inference may be performed in combination with the output result of the health condition diagnosis program, and the result may be output as a diagnosis result.

[0059] [Effect description] The health condition monitoring device 10 of this embodiment can detect specific behaviors of individuals belonging to a herd and extract, for example, individuals in an abnormal state. This makes it possible to take measures such as eliminating stress factors for the extracted individual in an abnormal state at an early stage. At the same time, it is possible to prevent stress from being applied to individuals around the abnormal individual, allowing the entire herd to behave in a healthy state.

[0060] [Third embodiment] In the third embodiment, a health condition assessment device 10 is provided that estimates and diagnoses the health condition based on the acquired behavioral data, and acquires basic information (basic animal information) including information normally published in a medical record, such as the animal's physique (weight, body length, etc.), age, sex, etc., and history of past treatments (medication history, etc.), and stores this information together with the behavioral data and health condition or diagnosis results, thereby extracting individuals with basic information similar to that of a selected individual and predicting the future health condition of the selected individual.

[0061] 9 is a block diagram showing an example of the configuration of a health condition determination device 10 according to the third embodiment. The health condition determination device 10 according to this embodiment has the following configuration. That is, as shown in FIG. 9, the health condition determination device 10 according to the third embodiment has a behavioral data acquisition unit 11, a behavioral data accumulation unit 12, a health condition estimation unit 13, and a health condition diagnosis unit 14. The configuration of the health condition determination device 10 according to this embodiment differs from that of the above-described embodiment in that it newly includes an animal basic information receiving unit 17, an animal basic information accumulation unit 18, a similar individual extraction unit 19, and a health condition prediction unit 20.

[0062] The animal basic information receiving unit 17 receives animal basic information including at least one of information about the attributes of a plurality of animals, information about their physique, and information about their treatment history. "Information about attributes" refers to information such as age, sex, and place of birth, while "information about physique" refers to information such as body length, weight, and waist circumference, and "information about treatment history" refers to information about past illnesses and their corresponding diagnosis results, as well as details of treatment (e.g., medication history). In this embodiment, "treatment history" also includes a history of preventive medical care such as vaccinations.

[0063] "Accept" means to input information, which may be input manually using an input device of an input / output interface such as a keyboard, or may be input automatically, for example, by connecting to a database of an electronic medical record held by a veterinarian to obtain the data. The input information is stored in the animal basic information storage unit 18, which will be described later.

[0064] The animal basic information storage unit 18 stores animal basic information. "Storage" means storing the information, including the history, in a memory area, and in principle, the data is not overwritten. The stored animal basic information may be linked to behavioral data, health status data, diagnostic results, etc., using data such as an animal ID.

[0065] The similar individual extraction unit 19 extracts similar individuals, which are animals with similar basic animal information, based on the animal basic information and the animal's health condition. That is, it is possible to extract individuals with similar basic animal information to a certain animal and in a predetermined health condition. For example, it is possible to extract individuals with similar body length, weight, and age and whose daily food intake exceeds 1.0 kg. Although the extraction process is based on the animal's health condition, similar individuals may also be extracted based on diagnostic results according to the health condition. Furthermore, the extraction of similar individuals may involve extracting individuals similar to a selected animal from the animals stored in the animal basic information storage unit 18.

[0066] Since the basic animal information is composed of data including past history, it is possible to extract similar individuals based on their past history and health status. For example, when extracting individuals similar to an individual 6 months old suffering from a disease, it is possible to extract individuals that are currently 2 years old but suffered from the same disease when they were 6 months old.

[0067] The health condition prediction unit 20 predicts the health condition of the one animal based on the basic animal information and health conditions of similar individuals. For example, it is possible to select an individual in good health from the diagnosis results, extract similar individuals from the basic animal information of that individual, and determine a treatment plan for a newborn animal in poor health based on the treatment history of the healthy individual. It is also possible to select an individual in poor health from the diagnosis results, extract individuals with similar basic animal information and health condition trends to that of the selected individual, and provide warnings.

[0068] These predictions may be made by extracting similar individuals for each selected individual, or by using a statistical model. For example, data on basic animal information and health condition information may be converted into quantum vectors, the data may be subjected to cluster analysis to form clusters, and the health condition of individuals belonging to the same cluster may be referenced to predict the health condition. Alternatively, the center of gravity of the vectors of individuals that are elements forming the clusters may be found, a group of categorized models may be generated for each cluster, and the model closest to the selected individual may be referenced to predict the health condition or select a treatment method.

[0069] FIG. 10 is a schematic diagram showing an overview of the processing of the health condition determination device 10 in the third embodiment. As shown in this diagram, first, processing such as acquisition / accumulation of behavioral data, estimation of health condition, and diagnosis of health condition is executed. These processing have already been explained in the above embodiments, so description will be omitted. Next, the animal basic information accepting unit 17 accepts input of attribute information such as age / gender, information related to physique such as body length / weight, etc. The accepted information is accumulated in the animal basic information accumulation unit 18. It is desirable that this information be input and accumulated periodically from birth. If the health condition deteriorates and treatment / medication is received, input of such information is accepted each time.

[0070] The similar individual extraction unit 19 selects individual a. It is 0 years and 6 months old, and a health diagnosis indicates that it is suspected of having △△ disease. The similar individual extraction process extracts individual c, who is currently 2 years and 10 months old and healthy. The two individuals are the same breed and sex, and their weights at the time differed by 3 kg, with an approximate age of 6 months. Furthermore, c is suffering from △△ disease and has been administered with □□ drug. Referring to the animal's basic information at 8 months old, two months after c, it is recorded that □□ drug was administered. Furthermore, since its weight has increased by 5 kg, it can be inferred that it has recovered from △△ disease and is growing healthily. From this information, it can be predicted that individual a will also recover from △△ disease if it is similarly treated with □□ drug. It can also be predicted that its health will improve and its weight will increase.

[0071] [Explanation of operation] An example of the operation of the health condition determination device 10 of this embodiment will be described with reference to FIG. 11. FIG. 11 is a flowchart showing an example of the operation of the health condition determination device 10 according to the third embodiment. As shown in this figure, first, basic information about an animal is received (step S1101). Next, the received basic information is accumulated (stored in a memory area) (step S1102). Following or in parallel with the above process, behavioral data of multiple animals is acquired (step S1103). Next, the acquired behavioral data of multiple animals is accumulated (stored) (step S1104). Thereafter, health condition estimation (step S1105) and health condition diagnosis (step S1106) are performed.

[0072] Next, one animal is selected for which health condition prediction is to be performed (step S1107). As indicated by the dotted line, the processes from acquiring behavioral data of multiple animals (step S1103) to diagnosing the health condition (step S1106) may be performed in parallel or in advance and completed before this process (step S1107) is performed. Next, similar individuals similar to the selected individual are extracted (step S1108). Finally, health condition prediction is performed using the basic animal information, behavioral data, health condition, and health condition diagnosis results of the similar individuals (step S1109).

[0073] [Hardware configuration] The health condition determination device 10 of this embodiment can be configured by an information processing device (computer), and has the configuration illustrated in FIG. 5, similar to the first and second embodiments.

[0074] The functions of the health status determination device 10 of this embodiment are realized by a group of programs (processing modules) stored in memory 52, such as an animal basic information reception program, a behavioral data acquisition program, a health status estimation program, a health status diagnosis program, a similar individual extraction program, a health status prediction program, etc., and a group of data including accumulated behavioral data, animal basic information data, etc.

[0075] [Hardware operation] When the health condition determination device 10 starts operating, an animal basic information receiving program is called from memory 52 and executed by the CPU 51. This program receives the information in the form of data from an input device such as a keyboard on the input / output interface 53, or via the network or NIC 54, and stores and accumulates it as animal basic information data in memory 52. ​​Next, a behavioral data acquisition program, a health condition estimation program, a health condition diagnosis program, etc. are called from memory 52 and run on the CPU 51, storing behavioral data in memory 52 and outputting the health condition, health condition diagnosis results, etc. The operation of these hardware components has been explained in the above embodiment, so a detailed explanation will be omitted.

[0076] Next, the similar individual extraction program is called from memory 52 and executed by CPU 51. This program accepts the selection of an individual via input from a keyboard or the like of input / output interface 53. Next, it references the basic animal information data related to that individual and extracts individuals with similar basic animal information data through calculations. Next, the health condition prediction program is called from memory 52 and executed by CPU 51. This program references the accumulated basic animal information data, health condition data, and health condition diagnosis results data of the extracted similar individual, obtains the health condition, such as future diseases, and outputs this as predicted data for the selected individual to a display device or the like.

[0077] [Effect description] The health condition determination device 10 of this embodiment extracts individuals similar to a selected individual and makes it possible to predict the future health condition of the individual based on the accumulated basic animal information data, etc. This makes it possible to detect future risks from extracted similar individuals in poor health, and to take measures for the selected individual based on the treatments, etc. accumulated in the basic animal information data, from extracted similar individuals in good health.

[0078] Some or all of the above-described embodiments can also be described as in the following supplementary notes. However, the following supplementary notes are merely examples of the present invention, and the present invention is not limited to such cases. [Appendix 1] This is the same as the health condition monitoring device according to the first aspect described above. [Appendix 2] Preferably, the health condition monitoring device according to claim 1 further comprises a health condition diagnosis unit that diagnoses the health condition of the animal based on the health condition. [Appendix 3] Preferably, the health condition assessment device according to claim 2, wherein the health condition assessment unit calculates a health degree index value that is an index value indicating the degree of health of the animal based on the health condition. [Appendix 4] The behavioral data acquisition unit acquires behavioral data of a plurality of animals, the behavioral data storage unit stores the behavioral data of a plurality of animals, and the health state estimation unit estimates the health states of the plurality of animals using the behavioral data of the plurality of animals, preferably a health state assessment device according to any one of Appendices 1 to 3. [Appendix 5] Preferably, the health condition monitoring device according to claim 4, further comprising a group detection unit that detects a group of animals, and the behavioral data acquisition unit acquires behavioral data of a plurality of animals that belong to the same group. [Appendix 6] The health condition monitoring device according to claim 4 or 5, further comprising a specific individual extraction unit that extracts an individual animal in a specific state from the plurality of animals using behavioral data of the plurality of animals. [Appendix 7] Preferably, the health status monitoring device according to any one of appendices 4 to 6 further comprises an animal basic information receiving unit that receives animal basic information including at least one of information on the attributes of a plurality of animals, information on physique, and information on treatment history; an animal basic information storage unit that stores the animal basic information; and a similar individual extraction unit that extracts similar individuals that are animals with similar animal basic information based on the animal basic information and the health status of the animals. [Appendix 8] Preferably, the health condition monitoring device of Appendix 7 further includes a health condition prediction unit that extracts similar individuals that are similar to one selected animal from among a plurality of animals and predicts the health condition of the selected animal based on the animal basic information and health condition of the similar individuals. [Appendix 9] This is the same as the method for understanding health status related to the second aspect described above. [Appendix 10] This is the same as the program related to the third perspective mentioned above. Note that Supplementary Notes 9 and 10 can be expanded into Supplementary Notes 2 to 8, just like Supplementary Note 1.

[0079] The disclosures of the above-cited patent documents and other documents are incorporated herein by reference. Modifications and adjustments of the embodiments and examples are possible within the scope of the entire disclosure of the present invention (including the claims), and further based on the basic technical concepts thereof. Furthermore, various combinations and selections (including partial deletions) of various disclosed elements (including elements of each claim, each element of each embodiment or example, each element of each drawing, etc.) are possible within the scope of the entire disclosure of the present invention. In other words, the present invention naturally includes various modifications and alterations that would be possible by a person skilled in the art in accordance with the entire disclosure and technical concepts, including the claims. In particular, with regard to the numerical ranges set forth herein, any numerical value or subrange included within the range should be construed as specifically set forth, even if not otherwise specified. [Explanation of symbols]

[0080] 10 Health status monitoring device 11 Behavioral data acquisition unit 12 Behavioral Data Storage Unit 13 Health Status Estimation Department 14 Health Checkup Department 15 Specific individual extraction unit 16 group detection unit 17 Animal Basic Information Reception Department 18 Basic Animal Information Storage Department 19 Similar individual extraction unit 20 Health Status Prediction Department 51 CPU 52 memory 53 Input / Output Interface 54 NIC 55 Internal Bus

Claims

1. A behavioral data acquisition unit that acquires behavioral data indicating the behavior of livestock by performing at least one of monitoring and sensing on the livestock; a behavioral data storage unit that stores the behavioral data; a health condition estimation unit that estimates the health condition of the livestock using the behavioral data; a health condition diagnosis unit that diagnoses the health condition of the livestock based on the health condition; a herd detection unit that identifies a physical range from the results of the monitoring or sensing and detects a plurality of the livestock located within the physical range as a herd; a specific individual extraction unit that extracts individuals in a specific state from the plurality of livestock belonging to the group using the behavioral data of the plurality of livestock belonging to the group, the health condition assessment unit evaluates the health condition in accordance with predetermined standards or rules and presents predetermined necessary measures in accordance with the evaluation; the behavioral data acquisition unit acquires the behavioral data of the plurality of livestock belonging to the same group; the behavioral data storage unit stores the behavioral data of the plurality of livestock belonging to the group; The health condition estimation unit is a health condition grasping device that estimates the health conditions of the multiple livestock belonging to the group using the behavioral data of the multiple livestock belonging to the group.

2. The health condition monitoring device of claim 1, wherein the health condition diagnosis unit diagnoses the health condition by comparing past data of the livestock from which the behavioral data is obtained, or by comparing data of an individual different from the livestock from which the behavioral data is obtained on the same date and time.

3. 2. The health condition determining device according to claim 1, wherein the health condition diagnosing unit calculates a health degree index value, which is an index value indicating the degree of health of the livestock, based on the health condition.

4. an animal basic information receiving unit that receives animal basic information including at least any of information on the attributes of the plurality of livestock, information on physique, and information on treatment history; an animal basic information storage unit that stores the animal basic information; The health condition monitoring device of claim 1, further comprising a similar individual extraction unit that extracts similar individuals, which are livestock individuals having similar animal basic information, based on the animal basic information and the health condition of the livestock.

5. the similar individual extraction unit extracts the similar individual that is similar to one livestock selected from the plurality of livestock; 5. The health condition monitoring device according to claim 4, further comprising a health condition prediction unit that predicts the health condition of the one livestock based on the basic animal information and the health condition of the similar individual.

6. A behavioral data acquisition step of acquiring behavioral data indicating the behavior of livestock, the behavioral data being acquired by performing at least one of monitoring or sensing on the livestock; a herd detection step of identifying a physical range from the results of the monitoring or sensing and detecting a plurality of the livestock located within the physical range as a herd; a behavioral data storage step of storing the behavioral data in a storage area; a health condition estimation step of estimating the health condition of the livestock using the behavioral data; a specific individual extraction step of extracting individuals in a specific state from the plurality of livestock belonging to the group using the behavioral data of the plurality of livestock belonging to the group; a health condition diagnosis step of diagnosing the health condition of the livestock based on the health condition, In the behavioral data acquisition step, the behavioral data of the plurality of livestock belonging to the same group is acquired, In the behavioral data accumulation step, the behavioral data of the plurality of livestock belonging to the group is stored in the storage area for accumulation; In the health condition estimation step, the health conditions of the livestock belonging to the group are estimated using the behavioral data of the livestock belonging to the group, and the health conditions are evaluated in accordance with predetermined standards or rules, and predetermined necessary measures are presented based on the evaluation.

7. A program for causing a computer to execute the health status assessment method described in claim 6.

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