Real-time Monitoring System and Method for the Health of Animal Individuals Based on Smart Wearable Devices

Abstract

The present invention discloses a real-time monitoring system and method for the health of individual animals based on intelligent wearable devices, belonging to the field of animal health monitoring. The present invention obtains the physiological data and behavioral data of animals, generates the state vectors of animals, constructs a physical sign similarity evaluation model, imports the state vectors of animals into the physical sign similarity evaluation model to evaluate the state similarity between animals, constructs an individual infection model, imports the physical sign similarity between animals into the individual infection model to evaluate the individual infection ability of animals, constructs a disease transmission model, imports the individual infection ability of infected animals into the disease transmission model to evaluate the infection risk of other animals, constructs an infection warning model, and imports the animal infection probability into the infection warning model for warning. The present invention warns of animal infectious disease situations through real-time monitoring and analysis of animal health, behavior, environment, and disease transmission laws.

Description

Technical Field

[0001] The present invention belongs to the field of animal health monitoring, and specifically relates to a real-time monitoring system and method for the individual health of animals based on intelligent wearable devices. Background Art

[0002] With the rapid development of modern animal husbandry, animal diseases have become an important factor affecting breeding efficiency. Traditional breeding methods mainly rely on manual inspections and regular quarantines, and these methods have certain limitations, such as slow response speed, high risk of missed diagnosis and omission.

[0003] Although existing disease transmission models can describe the transmission process of diseases in a group to a certain extent, these models often assume that the transmission speed and contact probability are constant, and ignore the influence of differences in individual health status, changes in behavior patterns, and environmental factors on transmission. Especially in the actual breeding process, the health status, environmental changes, and behavior patterns of the animal group are dynamically changing, and traditional models cannot accurately reflect the influence of these factors. The present invention realizes disease transmission early warning, accurate prediction, and scientific prevention and control through real-time monitoring of animal health, behavior, environment, and disease transmission laws. Summary of the Invention

[0004] Aiming at the deficiencies of the existing technology, the present invention proposes a real-time monitoring system and method for the individual health of animals based on intelligent wearable devices.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A real-time monitoring method for the individual health of animals based on intelligent wearable devices, which includes the following specific steps:

[0007] Obtain the physiological data and behavior data of the animal, and generate a state vector of the animal;

[0008] Construct a physical sign similarity evaluation model, and import the state vector of the animal into the physical sign similarity evaluation model to evaluate the state similarity between animals;

[0009] Construct an individual infection model, and import the physical sign similarity between animals into the individual infection model to evaluate the individual infection ability of animals;

[0010] Construct a disease transmission model, and import the individual infection ability of the infected animal into the disease transmission model to evaluate the infection risk of other animals;

[0011] Construct an infection early warning model, and import the animal infection probability into the infection early warning model for early warning.

[0012] Preferably, the step of obtaining the physiological data and behavior data of the animal and generating a state vector of the animal includes the following specific steps:

[0013] S11. Obtain the physiological data and behavioral data of the animal through the intelligent wearable device, and at the same time collect the environmental data of the animal's residence through the environmental monitoring module. Among them, the physiological data includes body temperature, heart rate, and respiratory rate, and the behavioral data includes exercise amount, water intake, and food intake;

[0014] S12. Generate a physiological parameter vector from the obtained physiological data of the animal, and generate a behavioral parameter vector from the obtained behavioral data of the animal. Among them, the physiological parameter vector of the i-th animal is: , and the behavioral parameter vector of the i-th animal is: , where a is the body temperature, b is the heart rate, c is the respiratory rate, d is the exercise amount, e is the food intake, and f is the water intake;

[0015] S13. Combine the physiological parameter vector and the behavioral parameter vector to form the state vector of the animal. Among them, the state vector of the i-th animal is expressed as: .

[0016] Preferably, the steps for constructing the physical sign similarity evaluation model and importing the state vector of the animal into the physical sign similarity evaluation model to evaluate the state similarity between animals are as follows:

[0017] Substitute the state vectors between animals into the cosine similarity calculation formula between animals to calculate the similarity degree of animal physical signs. The physical sign similarity between the i-th infected animal and the j-th animal is: , where is the state vector of the i-th infected animal, is the state vector of the j-th animal, and are the norms of the state vectors of the i-th infected animal and the j-th animal respectively.

[0018] Preferably, the steps for constructing the individual infection model and importing the physical sign similarity between animals into the individual infection model to evaluate the individual infection ability of animals are as follows:

[0019] S31. Substitute the monitored temperature-humidity index and the ammonia concentration in the animal's residence into the environmental index calculation formula to evaluate the environment where the animal is located. The environmental index calculation formula for the animal's residence is: , where is the ammonia concentration in the animal's residence, is the ammonia concentration threshold in the animal's residence, THI is the temperature-humidity index in the animal's residence, and are the weights. The environment of the animal's residence is evaluated jointly by the temperature-humidity index and the ammonia concentration in the animal's residence. The higher the value, the stronger the promotion effect of the environment on the spread of the disease and the increased infection risk;

[0020] S32. Substitute the physical sign similarity between the \(i\)-th infected animal and the \(j\)-th animal into the individual infectious ability formula to evaluate the individual infectious ability of the \(i\)-th infected animal. The individual infectious ability evaluation formula of the \(i\)-th infected animal is as follows: , where is the basic pathogen infection rate, \(k\) is the latency adjustment factor, is the latency period, \(P\) is the duration of the \(i\)-th animal showing infection symptoms. The infection ability of the infected animal is comprehensively evaluated through the animal residence environment, the basic pathogen infection rate, and the physical sign similarity. The higher the similarity between an animal individual and an infected animal, the stronger the infectivity. And the influence of the latency period is controlled by adjusting the latency period duration. The infectivity reaches the peak in the later stage of the latency period.

[0021] Preferably, for the construction of the disease transmission model, importing the individual infectious ability of the infected animal into the disease transmission model to evaluate the infection risk of other animals includes the following specific steps:

[0022] S41. Substitute the individual infectious ability of the \(i\)-th infected animal into the spatio-temporal transmission dynamics formula to evaluate the infection probability of the infected animal to other animals. The spatio-temporal transmission dynamics formula is as follows: , where is the infection probability of the \(j\)-th animal at time \(t\), \(N\) is the number of infected animals that have come into contact with the \(j\)-th animal, is the contact frequency between the \(i\)-th infected animal and the \(j\)-th animal, is the group recovery rate of the infectious disease. Among them, the calculation formula for the contact frequency between the \(i\)-th infected animal and the \(j\)-th animal is: , where is the overlapping duration of the movement trajectories of the \(i\)-th animal and the \(j\)-th animal within time \(T\), is the distance attenuation coefficient, is the distance between the \(i\)-th infected animal and the \(j\)-th animal. The animal intersections are judged through the movement trajectories monitored by the intelligent wearable device. Since an animal individual comes into contact with the surrounding infected animals and the virus carried by the infected animals is easily transmitted, the self-infection probability of the animal is increased according to the infectious ability and contact frequency of the infected animal. At the same time, due to the herd immunity and recovery of the animal group, the infection probability decays over time, and the decay rate is determined by the recovery rate;

[0023] S42. Differentiate the spatio-temporal transmission dynamics formula to obtain the infection probability of the \(j\)-th animal at time \(t\) , and evaluate the infection risk of the \(j\)-th animal at time \(t\).

[0024] Preferably, for the construction of the infection warning model, importing the animal infection probability into the infection warning model for warning includes the following specific steps:

[0025] S51. Compare the animal infection probability with the infection probability threshold. If it exceeds the threshold range, immediately isolate the animal, sample and test for pathogens, and carry out preventive treatment. If it is within the threshold range, strengthen the detection of physiological parameters and behavioral parameters;

[0026] S52. Substitute the number of early-warning animals into the formula for calculating the herd infection rate to evaluate the herd infection rate. The formula for calculating the herd infection rate is: , where V is the number of early-warning animals, Q is the number of infected animals, and M is the total number of animals. Take emergency measures for the animals according to the herd infection rate.

[0027] The real-time animal individual health monitoring system based on intelligent wearable devices is implemented based on the above-mentioned real-time animal individual health monitoring method based on intelligent wearable devices, and specifically includes:

[0028] The data acquisition module is used to acquire the physiological data and behavioral data of the animal and generate the state vector of the animal;

[0029] The physical sign similarity evaluation module is used to evaluate the state similarity between two animals;

[0030] The individual infectivity evaluation module is used to evaluate the individual infectivity of the animal;

[0031] The disease transmission module is used to evaluate the infection risk of other animals;

[0032] The infection early-warning module is used for early warning of infected animals and herd infection.

[0033] An electronic device includes: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory;

[0034] The processor executes the above-mentioned real-time animal individual health monitoring method based on intelligent wearable devices by calling the computer program stored in the memory.

[0035] A computer-readable storage medium is characterized in that it stores instructions, and when the instructions run on a computer, the computer is made to execute the above-mentioned real-time animal individual health monitoring method based on intelligent wearable devices.

[0036] Compared with the prior art, the beneficial effects of the present invention are:

[0037] The present invention obtains the physiological data and behavioral data of animals, generates the state vectors of animals, constructs a disease similarity evaluation model, imports the state vectors of animals into the disease similarity evaluation model to evaluate the state similarity between two animals, constructs an individual infection model, imports the disease similarity between animals into the individual infection model to evaluate the individual infection ability of animals, constructs a disease transmission model, imports the individual infection ability of infected animals into the disease transmission model to evaluate the infection risk of other animals, constructs an infection warning model, and imports the infection probability of animals into the infection warning model for warning. The present invention warns of animal infectious diseases through real-time monitoring and analysis of the health, behavior, environment, and disease transmission laws of animal groups. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the overall process of the method for real-time monitoring of the individual health of animals based on intelligent wearable devices according to the present invention;

[0039] Figure 2 It is a schematic diagram of the distance between an infected animal and other animals;

[0040] Figure 3 It is an overlapping graph of the trajectories of an infected animal and other animals;

[0041] Figure 4 It is a schematic diagram of the overall framework of the system for real-time monitoring of the individual health of animals based on intelligent wearable devices according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0043] Embodiment 1

[0044] The implementation scenario of this embodiment is as Figure 2-3 shown, specifically: the positions of infected animals and other animals are monitored through intelligent wearable devices, and the distance and trajectory overlap duration between them are obtained, and the infection effect of infected animals on other animals is comprehensively evaluated through the distance and overlap duration.

[0045] Please refer to Figure 1 , an embodiment provided by the present invention: a method for real-time monitoring of the individual health of animals based on intelligent wearable devices, which includes the following specific steps:

[0046] Obtain the physiological data and behavioral data of animals, and generate the state vectors of animals;

[0047] Construct a physical sign similarity evaluation model, and import the state vectors of animals into the physical sign similarity evaluation model to evaluate the state similarity between animals;

[0048] Construct an individual infection model, and import the physical sign similarity between animals into the individual infection model to evaluate the individual infection ability of animals;

[0049] Construct a disease transmission model, and import the individual infection ability of infected animals into the disease transmission model to evaluate the infection risk of other animals;

[0050] Construct an infection early warning model, and import the animal infection probability into the infection early warning model for early warning.

[0051] In this embodiment, it should be specifically noted that obtaining the physiological data and behavioral data of animals and generating the state vector of animals includes the following specific steps:

[0052] S11. Obtain the physiological data and behavioral data of animals through intelligent wearable devices, and at the same time collect the environmental data of the animal residence through the environmental monitoring module. Among them, the physiological data includes body temperature, heart rate, and respiratory rate, and the behavioral data includes exercise amount, water intake, and food intake;

[0053] S12. Generate a physiological parameter vector from the obtained physiological data of animals, and generate a behavioral parameter vector from the obtained behavioral data of animals. Among them, the physiological parameter vector of the i-th animal is: , and the behavioral parameter vector of the i-th animal is: , where a is body temperature, b is heart rate, c is respiratory rate, d is exercise amount, e is food intake, and f is water intake;

[0054] S13. Combine the physiological parameter vector and the behavioral parameter vector to form the state vector of animals. Among them, the state vector of the i-th animal is expressed as: .

[0055] In this embodiment, it should be specifically noted that constructing a physical sign similarity evaluation model and importing the state vector of animals into the physical sign similarity evaluation model to evaluate the state similarity between animals includes the following specific steps:

[0056] Substitute the state vectors between animals into the cosine similarity calculation formula between animals to calculate the similarity degree of animal physical signs. The physical sign similarity between the i-th infected animal and the j-th animal is: , where is the state vector of the i-th infected animal, is the state vector of the j-th animal, and are the norms of the state vectors of the i-th infected animal and the j-th animal respectively. By calculating the physical sign similarity between the infected animal and the individual animal, evaluate the similarity of the trait manifestations between the infected individual and the normal individual.

[0057] In this embodiment, it should be specifically noted that constructing an individual infection model and importing the physical sign similarity between animals into the individual infection model to evaluate the individual infection ability of animals includes the following specific steps:

[0058] S31. Substitute the monitored temperature-humidity index and the ammonia concentration in the animal residence into the environmental index calculation formula to evaluate the environment where the animal is located. Among them, the environmental index calculation formula for the animal residence is: , where is the ammonia concentration in the animal residence, is the ammonia concentration threshold in the animal residence, THI is the temperature-humidity index in the animal residence, and are weights, and The values of and are obtained from historical data and expert evaluation. The environment of the animal residence is evaluated jointly by the temperature-humidity index and the ammonia concentration in the animal residence. The higher the value, the stronger the promoting effect of the environment on the spread of diseases, increasing the infection risk. Among them, the temperature-humidity index is obtained by a temperature-humidity sensor;

[0059] S32. Substitute the physical sign similarity between the i-th infected animal and the j-th animal into the individual infection ability formula to evaluate the individual infection ability of the i-th infected animal. Among them, the individual infection ability evaluation formula for the i-th infected animal is: , where is the basic pathogen infection rate, k is the latency adjustment factor used to control the time decay rate, is the latency period, P is the duration of the i-th animal showing infection symptoms. The infection ability of the infected animal is comprehensively evaluated through the environment of the animal residence, the basic pathogen infection rate, and the physical sign similarity. The higher the similarity between the animal individual and the infected animal, the stronger the infectivity. And the influence of the latency period is controlled by adjusting the latency period duration. The infectivity reaches the peak in the later stage of the latency period.

[0060] In this embodiment, it should be specifically noted that constructing a disease transmission model and importing the individual infection ability of the infected animal into the disease transmission model to evaluate the infection risk of other animals includes the following specific steps:

[0061] S41. Substitute the individual infection ability of the i-th infected animal into the spatio-temporal transmission dynamics formula to evaluate the infection probability of the infected animal to other animals. Among them, the spatio-temporal transmission dynamics formula is: , where is the infection probability of the j-th animal at time t, N is the number of infected animals that have come into contact with the j-th animal, is the contact frequency between the i-th infected animal and the j-th animal, is the group recovery rate of the infectious disease. Among them, the calculation formula for the contact frequency between the i-th infected animal and the j-th animal is: , where is the overlapping duration of the movement trajectories of the i-th animal and the j-th animal within time T, is the distance attenuation coefficient, is the distance between the i-th infected animal and the j-th animal. The intersection of animals is judged through the movement trajectories monitored by intelligent wearable devices. Since an individual animal comes into contact with the surrounding infected animals and the virus carried by the infected animals is easily transmitted, the self-infection probability of the animal is increased according to the infectious ability and contact frequency of the infected animal. At the same time, due to herd immunity and recovery of the animal population, the infection probability decays over time, and the decay rate is determined by the recovery rate. Therefore, the formula is corrected by the infection decay term in the formula;

[0062] S42. Differentiate the spatio-temporal transmission dynamics formula to obtain the infection probability of the j-th animal at time t , and evaluate the infection risk of the j-th animal at time t.

[0063] It should be specifically noted in this embodiment that constructing an infection warning model and importing the animal infection probability into the infection warning model for warning includes the following specific steps:

[0064] S51. Compare the animal infection probability with the infection probability threshold. If it exceeds the threshold range, immediately isolate, sample and detect the pathogen, and carry out preventive treatment. If it is within the threshold range, strengthen the detection of physiological parameters and behavior parameters;

[0065] S52. Substitute the number of warning animals into the formula for calculating the herd infection rate to evaluate the herd infection rate. Among them, the formula for calculating the herd infection rate is: , where V is the number of warning animals, Q is the number of infected animals, and M is the total number of animals. Compare the herd infection rate with the herd infection threshold, and issue a warning to the breeder according to the herd infection rate, and take emergency measures for the animals.

[0066] It should be noted here that the value-taking method of the infection probability threshold is as follows: Obtain representative historical animal infection data and import it into the spatio-temporal transmission dynamics formula to calculate the infection probability. Obtain the evaluation of experts on these infection rates, infection ranges and intensities, and import the infection results into the fitting software to output the value-taking of the conforming infection probability threshold.

[0067] The advantages of this embodiment over the prior art are as follows: By evaluating the environmental conditions of the animal residence through the temperature-humidity index and the ammonia concentration in the animal residence, and introducing the environmental conditions of the animal residence, the basic pathogen infection rate, and the similarity of the signs between the animal individual and the infected animal into the individual infection model for comprehensive evaluation of the infection ability of the infected animal, the accuracy of monitoring the infection ability of animal individuals is improved. By introducing the infection ability, contact frequency of the infected animals contacted by the animal individual, and the disease recovery rate of the animal into the disease transmission model to evaluate the infection risk of other animals, and judging the animal intersection according to the movement trajectory monitored by the intelligent wearable device, the self-infection probability of the animal is increased based on the infection ability and contact frequency of the infected animal. At the same time, based on the herd immunity and recovery of the animal group, the infection probability decays over time, improving the accuracy of calculating the infection probability and further improving the accuracy of the warning effect.

[0068] Embodiment 2

[0069] As Figure 4 shown, an animal individual health real-time monitoring system based on an intelligent wearable device, which is implemented based on the above-mentioned animal individual health real-time monitoring method based on an intelligent wearable device, specifically includes a data acquisition module, a sign similarity evaluation module, an individual infection ability evaluation module, a disease transmission module, and an infection warning module. The data acquisition module is used to acquire the physiological data and behavioral data of the animal and generate a state vector of the animal; the sign similarity evaluation module is used to evaluate the state similarity between two animals, and the individual infection ability evaluation module is used to evaluate the individual infection ability of the animal; the disease transmission module is used to evaluate the infection risk of other animals; the infection warning module is used for infection warning of infected animals and animal groups.

[0070] Embodiment 3

[0071] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0072] The processor executes the above-mentioned animal individual health real-time monitoring method based on an intelligent wearable device by calling the computer program stored in the memory.

[0073] The electronic device may vary significantly due to different configurations or performances, and can include one or more processors (Central Processing Units, CPU) and one or more memories. Among them, at least one computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement the method for real-time monitoring of the health of animal individuals based on the intelligent wearable device provided in the above method embodiment. The electronic device can also include other components for realizing the functions of the device. For example, the electronic device can also have components such as wired or wireless network interfaces and input / output interfaces for data input and output. This embodiment will not be elaborated here.

[0074] Embodiment 4

[0075] This embodiment provides a computer-readable storage medium, on which a rewritable computer program is stored;

[0076] When the computer program runs on a computer device, the computer device is enabled to execute the above method for real-time monitoring of the health of animal individuals based on the intelligent wearable device.

[0077] For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device, etc.

[0078] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more collections of available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

Claims

1. A method for real-time monitoring of the health of individual animals based on intelligent wearable devices, characterized in that, It includes the following specific steps: Obtain the physiological data and behavioral data of the animal, and generate the state vector of the animal; It includes the following specific steps: Obtain the physiological data and behavioral data of the animal through the intelligent wearable device, and at the same time collect the environmental data of the animal's residence through the environmental monitoring module; The physiological parameter vector and the behavioral parameter vector are combined to form the state vector of the animal. Among them, the state vector of the i-th animal is expressed as: , where a is body temperature, b is heart rate, c is respiratory rate, d is exercise amount, e is food intake, and f is water intake; Construct a physical sign similarity evaluation model, and import the state vector of the animal into the physical sign similarity evaluation model to evaluate the state similarity between animals; It includes the following specific steps: Substitute the state vectors between animals into the cosine similarity calculation formula between animals to calculate the similarity degree of animal physical signs, calculate the physical sign similarity between the infected animal and the individual animal, and evaluate the state similarity between the infected individual and the normal individual; Construct an individual infection model, evaluate the environmental situation of the animal's residence through the temperature and humidity index and the ammonia concentration in the animal's residence, and import the environmental situation of the animal's residence, the basic pathogen infection rate, and the physical sign similarity between the animal individual and the infected animal into the individual infection model to comprehensively evaluate the infection ability of the infected animal; It includes the following specific steps: Obtain the temperature and humidity index and ammonia concentration of the animal's residence, evaluate the environmental situation of the animal's residence through the temperature and humidity index and the ammonia concentration of the animal's residence, and calculate the environmental index of the animal's residence through the animal residence environmental index calculation formula; Based on the environmental situation of the animal's residence, the basic pathogen infection rate, and the physical sign similarity between the animal individual and the infected animal, comprehensively evaluate the infection ability of the infected animal, obtain the physical sign similarity situation between the animal individual and the infected animal, control the influence of the incubation period on the animal's health status through the incubation period duration, and evaluate the infection ability of the infected animal in combination with the basic pathogen infection rate and the animal residence environmental index; Construct a disease transmission model, and import the infection ability, contact frequency of the infected animals contacted by the animal individual, and the disease recovery rate of the animal into the disease transmission model to evaluate the infection risk of other animals; It includes the following specific steps: S21. Substitute the individual infectivity of the \(i\)-th infected animal into the spatio-temporal transmission dynamics formula to evaluate the infection probability of the infected animal to other animals. The spatio-temporal transmission dynamics formula is as follows: , where is the infection probability of the \(j\)-th animal at time \(t\), \(N\) is the number of infected animals that have come into contact with the \(j\)-th animal, is the contact frequency between the \(i\)-th infected animal and the \(j\)-th animal, is the population recovery rate of the infectious disease. The calculation formula for the contact frequency between the \(i\)-th infected animal and the \(j\)-th animal is: , where is the overlapping duration of the movement trajectories of the \(i\)-th animal and the \(j\)-th animal within time \(T\), is the distance attenuation coefficient, is the distance between the \(i\)-th infected animal and the \(j\)-th animal; S22. Differentiate the spatio-temporal propagation dynamics formula to obtain the infection probability of the j-th animal at time t , and evaluate the infection risk of the j-th animal at time t; Construct an infection warning model, and import the animal infection probability into the infection warning model for warning.

2. The real-time animal individual health monitoring method based on a smart wearable device according to claim 1, wherein Constructing an infection warning model and importing the animal infection probability into the infection warning model for warning includes the following specific steps: Compare the animal infection probability with the infection probability threshold. If it exceeds the threshold range, immediately isolate, sample and detect the pathogen, and carry out preventive treatment. If it is within the threshold range, strengthen the detection of physiological parameters and behavioral parameters; Substitute the number of early-warning animals into the calculation formula of the group infection rate to evaluate the group infection rate. The calculation formula of the group infection rate is as follows: , where V is the number of early-warning animals, Q is the number of infected animals, and M is the total number of animals. An emergency plan is adopted for the animals according to the group infection rate.

3. The animal individual health real-time monitoring system based on the smart wearable device is implemented based on the animal individual health real-time monitoring method based on the smart wearable device according to any one of claims 1-2, and is characterized in that, Specifically, it includes: A data acquisition module, which is used to obtain the physiological data and behavioral data of the animal and generate the state vector of the animal; A physical sign similarity evaluation module, which is used to evaluate the state similarity between two animals; An individual infection ability evaluation module, which is used to evaluate the individual infection ability of the animal; A disease transmission module, which is used to evaluate the infection risk of other animals; An infection warning module, which is used for infection warning of infected animals and animal groups.

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