Wearable monitoring equipment for medium and large animals and working method

Abstract

The invention discloses a wearable monitoring device for medium and large animals and a working method, and particularly relates to the field of animal health monitoring. Comprising a sub-region division step, a sub-region equipment working information acquisition step, a sub-region data standardization processing step, a sub-region monitoring equipment comprehensive analysis step, a target region monitoring equipment comprehensive analysis step, a monitoring effect comprehensive judgment step and an interactive feedback step. According to the invention, through accurate area division, comprehensive monitoring of the target area, collection of comprehensive information including animal states, equipment performance and environmental data, a mathematical model is established to comprehensively evaluate the performance of the wearable monitoring equipment, and multi-dimensional measurement of the overall effect of the wearable monitoring equipment, comprehensive evaluation of the operation effect of the wearable monitoring equipment is realized. And the working efficiency and quality of equipment are effectively improved. The innovative method provides powerful support for field animal monitoring and animal husbandry management.

Description

Technical Field

[0001] The present invention relates to the technical field of animal health monitoring, and more specifically, to a wearable monitoring device and a working method for medium and large animals. Background Art

[0002] Wild animal monitoring is an important part of ecological research, wildlife protection, and biodiversity assessment. However, the wild environment is complex and changeable. Traditional manual monitoring methods are not only time-consuming and labor-intensive, but also difficult to achieve all-weather, all-round monitoring of animals. Therefore, it is particularly important to develop a wearable monitoring device that can adapt to the wild environment, is stable and reliable, and can transmit data in real time.

[0003] The wearable monitoring device has broad application prospects in wild animal monitoring. It can not only provide rich data support for ecological research and promote in-depth research on wild animal behavior habits and migration patterns, but also provide a powerful tool for wildlife protection, helping monitoring personnel to promptly discover and deal with illegal hunting, habitat destruction and other issues; at the same time, it can also provide a scientific basis for biodiversity assessment and promote the sustainable use and protection of natural resources.

[0004] However, there are still some shortcomings in its actual use. For example, the data collected by the existing technology is too single, which makes it difficult to accurately judge the overall situation of the wearable monitoring device. In addition, the current monitoring of wearable monitoring devices is mainly judged by a single dimension, such as GPS positioning information and animal vital signs information, and lacks comprehensive indicators. If monitoring is only carried out from a single dimension, the effect of the monitoring equipment and the influence of the animal's living environment are ignored, which in turn affects the ultimate practicality, work quality and efficiency of the wearable monitoring device. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a wearable monitoring device and a working method for medium and large animals, and solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a wearable monitoring device and working method for medium and large animals, comprising a sub-area division step, a sub-area equipment working information collection step, a sub-area data standardization processing step, a sub-area monitoring equipment comprehensive analysis step, a target area monitoring equipment comprehensive analysis step, a monitoring effect comprehensive judgment step and an interactive feedback step.

[0007] Preferably, step 1: sub-area division: used to record the animal population to be monitored as the target monitoring area, divide the target monitoring area into sub-monitoring areas according to different individuals, and mark them as 1, 2, 3...i in sequence;

[0008] Step 2: Sub-area equipment working information collection: including animal status information collection step, equipment information collection step and environment information collection step, used to collect data from the sub-area to obtain comprehensive parameters and output the comprehensive parameters to the sub-area data standardization processing step;

[0009] Step 3: Sub-area data standardization processing: It is used to standardize the collected data, eliminate the influence of dimension by performing Z-score standardization on the collected data, and output the processed data to the sub-area monitoring equipment comprehensive analysis step;

[0010] Step 4: Comprehensive analysis of sub-region monitoring equipment: used to import the data processed in the sub-region data standardization processing step into the mathematical model of the sub-region animal state coefficient, the mathematical model of the sub-region animal living environment coefficient, the mathematical model of the sub-region equipment quality coefficient and the mathematical model of the sub-region monitoring effect comprehensive index and calculate, to obtain the sub-region animal state coefficient, the sub-region animal living environment coefficient, the sub-region equipment quality coefficient and the sub-region monitoring effect comprehensive index;

[0011] Step 5: Comprehensive analysis of monitoring equipment in target area: used to import the data obtained from the comprehensive analysis step of sub-area monitoring equipment into the mathematical model of the comprehensive index of monitoring effect in target area and calculate it to obtain the comprehensive index of monitoring effect in target area;

[0012] Step 6: Comprehensive judgment of monitoring effect: used to compare the comprehensive index of monitoring effect of the target area with the preset value, and input the comparison result into the interactive feedback step;

[0013] Step 7: Interactive feedback: used to import the comparison results into the administrator terminal. When the comparison result of the comprehensive index of the monitoring effect of the target area is lower than the preset value, an alarm will be issued to the administrator's equipment.

[0014] Preferably, the specific method for acquiring the comprehensive parameters of each sub-region in the sub-region equipment working information acquisition step is as follows:

[0015] Comprehensive parameters refer to sub-area body temperature parameters, sub-area heart rate parameters, sub-area respiratory rate parameters, sub-area systolic pressure parameters, sub-area diastolic pressure parameters, sub-area daily drinking water frequency parameters, sub-area environmental temperature parameters, sub-area environmental humidity parameters, sub-area equipment location accuracy parameters, sub-area equipment information storage capacity parameters, sub-area equipment falling off probability parameters, and sub-area equipment failure rate parameters;

[0016] The sub-region body temperature parameter refers to the body temperature t of the i sub-region i ;

[0017] The sub-area heart rate parameter refers to the heart rate x of the i sub-areai ;

[0018] The sub-region respiratory frequency parameter refers to the respiratory frequency H of the sub-region i. i ;

[0019] The sub-region systolic pressure parameter refers to the systolic pressure of the sub-region i s i ;

[0020] The sub-region diastolic pressure parameter refers to the diastolic pressure z of the sub-region i. i ;

[0021] The sub-region daily drinking water frequency parameter refers to the daily drinking water frequency f of the i sub-region i ;

[0022] The sub-region ambient temperature parameter refers to the i sub-region ambient temperature T i ;

[0023] The sub-region environmental humidity parameter refers to the i sub-region environmental humidity W i ;

[0024] The sub-area device location accuracy parameter refers to the i sub-area device location accuracy wzjd i ;

[0025] The sub-area device information storage capacity parameter refers to the i sub-area device information storage capacity ccl i ;

[0026] The sub-area device dropout probability parameter refers to the device dropout probability P of the i-th sub-area device. t ;

[0027] The sub-region equipment failure rate parameter refers to the sub-region equipment failure rate P g .

[0028] Preferably, the sub-area device location accuracy parameter specifically refers to: a maximum error value between the actual GPS positioning of the device and the displayed positioning.

[0029] Preferably, the specific method for collecting the daily drinking water frequency parameter of the sub-area is as follows: using GPS to mark the water source near the device, and counting the number of times the animals go to the water source in a single day.

[0030] Preferably, the mathematical model of the sub-region animal state coefficient is as follows:

[0031] AM i refers to the animal status coefficient of sub-region i, t i Refers to the body temperature of the sub-region t i , X i Refers to the heart rate of the i sub-area, H i Refers to the respiratory rate of sub-area i, s irefers to the systolic pressure of the i sub-area, z i refers to the diastolic pressure in the i subregion, f i It refers to the frequency of drinking water in a single day in sub-area i, and t, s, z, H, and X refer to the average body temperature, systolic blood pressure, diastolic blood pressure, respiratory rate, and heart rate of the population in a healthy state, respectively.

[0032] Preferably, the mathematical model of the sub-region animal living environment coefficient is as follows:

[0033] Among them BM i Refers to the animal survival environment coefficient of sub-region i, T i Refers to the ambient temperature of the i-th sub-area, W i refers to the environmental humidity of sub-region i, T and W refer to the average temperature and humidity of the daily living environment of the population, respectively.

[0034] Preferably, the mathematical model of the sub-region equipment quality coefficient is as follows:

[0035] Among them, CM i Refers to the equipment quality coefficient of sub-area i, wzjd i Refers to the device location accuracy of the i sub-area, ccl i Refers to the storage capacity of device information in sub-area i, P t refers to the probability of device failure in sub-area i, P g Refers to the equipment failure rate in the sub-region.

[0036] Preferably, the mathematical model of the sub-region monitoring effect comprehensive index is as follows:

[0037] in Refers to the comprehensive index of monitoring effect in the sub-region, AM i Refers to the animal status coefficient of sub-region i, BM i Refers to the animal living environment coefficient of sub-region i, CM i It refers to the equipment quality coefficient of sub-area i, and α1, α2, and α3 refer to weight coefficients.

[0038] Preferably, the weight coefficients α1, α2, and α3 are calculated by an entropy method, and the specific calculation steps of the entropy method are as follows:

[0039] Data standardization: Since the measurement units of various indicators may be different, in order to eliminate the impact of the dimension, the collected data needs to be standardized. Commonly used standardization methods include Z-score standardization and range method standardization;

[0040] Calculate the proportion of indicators: Calculate the proportion of the i-th sample value under the j-th indicator to the sum of all sample values ​​of the indicator. This step is the basis for the subsequent calculation of information entropy;

[0041] Calculate information entropy: According to the definition and calculation formula of information entropy, calculate the information entropy ej of the jth indicator. The smaller the information entropy, the greater the degree of variation of the indicator and the greater the amount of information provided;

[0042] Calculate information entropy redundancy: Information entropy redundancy dj is the complement of information entropy, that is, dj = 1-ej. The greater the information entropy redundancy, the more information the indicator contains, and the greater the impact on the comprehensive evaluation;

[0043] Calculate weight: Calculate the weight of each indicator in the comprehensive evaluation according to its information entropy redundancy. The weight coefficient is the ratio of the information entropy redundancy of each indicator to the sum of the information entropy redundancy of all indicators.

[0044] Preferably, the mathematical model of the comprehensive index of the target area monitoring effect is as follows:

[0045] in Refers to the comprehensive index of monitoring effect in the target area. Refers to the comprehensive index of sub-region monitoring effect.

[0046] Preferably, the preset value is a warning value for evaluating the effectiveness of wearable monitoring equipment, the animal living environment, and the physical health of animals based on industry practical experience. When the comprehensive index of target area monitoring effect in the target area is lower than the preset value, it means that the effect of wearable monitoring equipment in this area is poor, the animal living environment is poor, and the physical health of animals is poor, and corresponding measures need to be taken to reduce the risk.

[0047] Preferably, when the comparison result of the interactive feedback step is lower than a preset value, the system will trigger an alarm function on the terminal, send a warning signal to the management personnel in the form of sound, vibration and pop-up window, and give relevant parameters, and use artificial intelligence to help management personnel analyze the reasons affecting the comprehensive index of the monitoring effect of the target area, and further track down specific aspects that affect the comprehensive performance, such as poor effect of wearable monitoring equipment, poor living environment of animals, and poor physical health of animals.

[0048] Technical effects and advantages of the present invention:

[0049] 1. The present invention realizes real-time and comprehensive monitoring of the target area through precise area division. The target area is divided into several sub-areas through the sub-area division module, and basic information is collected in each sub-area. The basic information includes sub-area body temperature information, sub-area heart rate information, sub-area respiratory rate information, sub-area systolic blood pressure information, sub-area diastolic blood pressure information, sub-area daily drinking water frequency information, sub-area environmental temperature information, sub-area environmental humidity information, sub-area equipment position accuracy information, sub-area equipment information storage capacity information, sub-area equipment shedding probability information, sub-area equipment failure rate information, covering the three aspects of animal status information, equipment information and environmental information of the wearable monitoring device, thereby providing a more comprehensive and detailed monitoring means for the overall performance of the wearable monitoring device;

[0050] 2. By conducting an in-depth analysis of the collected data, the present invention establishes a mathematical model that can comprehensively analyze the overall situation of the wearable monitoring device. By establishing such a comprehensive model, the present invention can better measure the overall effect of the wearable monitoring device from different dimensions. This comprehensive evaluation method can more comprehensively understand the comprehensive effect of the wearable monitoring device in the actual operation process, thereby improving the overall work efficiency and quality of the wearable monitoring device. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] As attached Figure 1 A wearable monitoring device and working method for medium and large animals shown in the figure include a sub-area division step, a sub-area equipment working information collection step, a sub-area data standardization processing step, a sub-area monitoring equipment comprehensive analysis step, a target area monitoring equipment comprehensive analysis step, a monitoring effect comprehensive judgment step and an interactive feedback step.

[0054] The sub-area division step is used to record the animal population to be monitored as the target monitoring area, divide the target monitoring area into sub-monitoring areas according to different individuals, and mark them as 1, 2, 3...i in sequence;

[0055] The sub-region equipment working information collection step includes an animal status information collection step, an equipment information collection step and an environment information collection step, which is used to collect data from the sub-region to obtain comprehensive parameters and output the comprehensive parameters to the sub-region data standardization processing step;

[0056] In a preferred technical solution of the present application, the specific method for obtaining the comprehensive parameters of each sub-area in the sub-area equipment working information collection step is as follows:

[0057] In this embodiment, it should be specifically explained that the comprehensive parameters refer to the sub-area body temperature parameter, the sub-area heart rate parameter, the sub-area respiratory rate parameter, the sub-area systolic pressure parameter, the sub-area diastolic pressure parameter, the sub-area daily drinking water frequency parameter, the sub-area ambient temperature parameter, the sub-area ambient humidity parameter, the sub-area device location accuracy parameter, the sub-area device information storage capacity parameter, the sub-area device fall-off probability parameter, and the sub-area device failure rate parameter;

[0058] The sub-region body temperature parameter refers to the body temperature t of the i sub-region i ;

[0059] The sub-area heart rate parameter refers to the heart rate x of the i sub-area i ;

[0060] The sub-region respiratory frequency parameter refers to the respiratory frequency H of the sub-region i. i ;

[0061] The sub-region systolic pressure parameter refers to the systolic pressure of the sub-region i s i ;

[0062] The sub-region diastolic pressure parameter refers to the diastolic pressure z of the sub-region i. i ;

[0063] The sub-region daily drinking water frequency parameter refers to the daily drinking water frequency f of the i sub-region i ;

[0064] The sub-region ambient temperature parameter refers to the i sub-region ambient temperature T i ;

[0065] The sub-region environmental humidity parameter refers to the i sub-region environmental humidity W i ;

[0066] The sub-area device location accuracy parameter refers to the i sub-area device location accuracy wzjd i ;

[0067] The sub-area device information storage capacity parameter refers to the i sub-area device information storage capacity ccl i ;

[0068] The sub-area device dropout probability parameter refers to the device dropout probability P of the i-th sub-area device.t ;

[0069] The sub-region equipment failure rate parameter refers to the sub-region equipment failure rate P g ;

[0070] It should be specifically explained in this embodiment that the sub-region body temperature parameter, sub-region heart rate parameter, sub-region respiratory rate parameter, sub-region systolic pressure parameter, sub-region diastolic pressure parameter, ambient temperature parameter, ambient humidity parameter, sub-region device position accuracy parameter, sub-region device information storage capacity parameter, sub-region device fall-off probability parameter, and sub-region device failure rate parameter are all obtained by conventional methods or conventional equipment, such as collecting ambient temperature parameters and ambient humidity parameters through built-in sensors of wearable monitoring equipment, so this embodiment does not specifically limit them;

[0071] It should be specifically explained in this embodiment that the sub-area device location accuracy parameter specifically refers to: the maximum error value between the actual location of the device GPS and the displayed location;

[0072] It should be specifically explained in this embodiment that the specific method of collecting the daily drinking water frequency parameter of the sub-area is as follows: using GPS to mark the water source near the device, and counting the number of times the animals go to the water source in a single day;

[0073] The sub-area data standardization processing step is used to standardize the collected data, and the effect of eliminating the influence of dimension is achieved by performing Z-score standardization on the collected data, and the processed data is output to the sub-area monitoring equipment comprehensive analysis step.

[0074] It should be specifically noted in this embodiment that Z-score standardization is a commonly used data preprocessing method, which converts the original data into a standardized Z-Score by calculating the mean and standard deviation of the original data. This method can eliminate the magnitude differences between data, so that data of different magnitudes can be compared and comprehensively analyzed.

[0075] The sub-region monitoring equipment comprehensive analysis step is used to import the data processed in the sub-region data standardization processing step into the mathematical model of the sub-region animal state coefficient, the mathematical model of the sub-region animal living environment coefficient, the mathematical model of the sub-region equipment quality coefficient and the mathematical model of the sub-region monitoring effect comprehensive index and calculate to obtain the sub-region animal state coefficient, the sub-region animal living environment coefficient, the sub-region equipment quality coefficient and the sub-region monitoring effect comprehensive index;

[0076] It should be specifically explained in this embodiment that the mathematical model of the sub-region animal state coefficient is as follows:

[0077] AM irefers to the animal status coefficient of sub-region i, t i Refers to the body temperature of the sub-region t i , X i Refers to the heart rate of the i sub-area, H i Refers to the respiratory rate of sub-area i, s i refers to the systolic pressure of the i sub-area, z i refers to the diastolic pressure in the i subregion, f i refers to the frequency of drinking water in a single day in the i sub-region, t, s, z, H, and X refer to the average body temperature, systolic blood pressure, diastolic blood pressure, respiratory rate, and heart rate of the population in a healthy state, respectively;

[0078] It should be specifically explained in this embodiment that the mathematical model of the sub-region animal living environment coefficient is as follows:

[0079] Among them BM i Refers to the animal survival environment coefficient of sub-region i, T i Refers to the ambient temperature of the i-th sub-area, W i refers to the environmental humidity of the i-th sub-region, T and W refer to the average temperature and humidity of the daily living environment of the population, respectively;

[0080] It should be specifically explained in this embodiment that the mathematical model of the sub-region equipment quality coefficient is as follows:

[0081] Among them, CM i Refers to the equipment quality coefficient of sub-area i, wzjd i Refers to the device location accuracy of the i sub-area, ccl i Refers to the storage capacity of device information in sub-area i, P t refers to the probability of device failure in sub-area i, P g Refers to the equipment failure rate in the sub-region;

[0082] It should be specifically explained in this embodiment that the mathematical model of the sub-region monitoring effect comprehensive index is as follows:

[0083] in Refers to the comprehensive index of monitoring effect in the sub-region, AM i Refers to the animal status coefficient of sub-region i, BM i Refers to the animal living environment coefficient of sub-region i, CM i refers to the equipment quality coefficient of sub-area i, α1, α2, and α3 refer to weight coefficients;

[0084] It should be specifically explained in this embodiment that the weight coefficients α1, α2, and α3 are calculated by an entropy method, and the specific calculation steps of the entropy method are as follows:

[0085] Data standardization: Since the measurement units of various indicators may be different, in order to eliminate the impact of the dimension, the collected data needs to be standardized. Commonly used standardization methods include Z-score standardization and range method standardization;

[0086] Calculate the proportion of indicators: Calculate the proportion of the i-th sample value under the j-th indicator to the sum of all sample values ​​of the indicator. This step is the basis for the subsequent calculation of information entropy;

[0087] Calculate information entropy: According to the definition and calculation formula of information entropy, calculate the information entropy ej of the jth indicator. The smaller the information entropy, the greater the degree of variation of the indicator and the greater the amount of information provided;

[0088] Calculate information entropy redundancy: Information entropy redundancy dj is the complement of information entropy, that is, dj = 1-ej. The greater the information entropy redundancy, the more information the indicator contains, and the greater the impact on the comprehensive evaluation;

[0089] Calculate weight: Calculate the weight of each indicator in the comprehensive evaluation according to its information entropy redundancy. The weight coefficient is the ratio of the information entropy redundancy of each indicator to the sum of the information entropy redundancy of all indicators.

[0090] The target area monitoring equipment comprehensive analysis step is used to import the data obtained in the sub-area monitoring equipment comprehensive analysis step into the mathematical model of the target area monitoring effect comprehensive index and perform calculations to obtain the target area monitoring effect comprehensive index;

[0091] It should be specifically explained in this embodiment that the mathematical model of the target area monitoring effect comprehensive index is as follows:

[0092] in Refers to the comprehensive index of monitoring effect in the target area. Refers to the comprehensive index of sub-region monitoring effect.

[0093] The monitoring effect comprehensive judgment step is used to compare the target area monitoring effect comprehensive index with the preset value, and input the comparison result into the interactive feedback step;

[0094] What needs to be specifically explained in this embodiment is that the preset value is a warning value for evaluating the effectiveness of wearable monitoring equipment, the living environment of animals, and the physical health of animals based on industry practical experience. When the comprehensive index of the target area monitoring effect in the target area is lower than the preset value, it means that the effect of the wearable monitoring equipment in the area is poor, the living environment of animals is poor, and the physical health of animals is poor, and corresponding measures need to be taken to reduce the risk.

[0095] The interactive feedback step is used to import the comparison result into the administrator terminal, and when the comparison result of the comprehensive index of the monitoring effect of the target area is lower than the preset value, an alarm will be issued to the administrator's equipment;

[0096] What needs to be specifically explained in this embodiment is that when the comparison result of the interactive feedback step is lower than the preset value, the system will trigger the alarm function on the terminal, send a warning signal to the management personnel through sound, vibration and pop-up window, and give relevant parameters, and use artificial intelligence to help management personnel analyze the reasons affecting the comprehensive index of the monitoring effect of the target area, and further track down the specific aspects that affect the comprehensive performance, such as poor effect of wearable monitoring equipment, poor living environment of animals, and poor physical health of animals.

[0097] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0098] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A wearable monitoring device and working method for medium and large animals, characterized in that: include: Sub-area division steps, sub-area equipment working information collection steps, sub-area data standardization processing steps, sub-area monitoring equipment comprehensive analysis steps, target area monitoring equipment comprehensive analysis steps, monitoring effect comprehensive judgment steps and interactive feedback steps; S1: Sub-area division: used to record the animal population to be monitored as the target monitoring area, divide the target monitoring area into sub-monitoring areas according to different individuals, and mark them as 1, 2, 3...i in sequence; S2: Sub-area equipment working information collection: including animal status information collection step, equipment information collection step and environment information collection step, used to collect data from the sub-area to obtain comprehensive parameters and output the comprehensive parameters to the sub-area data standardization processing step; S3: Sub-area data standardization processing: used to standardize the collected data, eliminate the effect of dimension by performing Z-score standardization on the collected data, and output the processed data to the comprehensive analysis step of the sub-area monitoring equipment; S4: Comprehensive analysis of sub-region monitoring equipment: used to import the data processed in the sub-region data standardization processing step into the mathematical model of the sub-region animal state coefficient, the mathematical model of the sub-region animal living environment coefficient, the mathematical model of the sub-region equipment quality coefficient and the mathematical model of the sub-region monitoring effect comprehensive index and calculate, to obtain the sub-region animal state coefficient, the sub-region animal living environment coefficient, the sub-region equipment quality coefficient and the sub-region monitoring effect comprehensive index; S5: Comprehensive analysis of monitoring equipment in target area: used to import the data obtained from the comprehensive analysis step of sub-area monitoring equipment into the mathematical model of the comprehensive index of monitoring effect in target area and perform calculation to obtain the comprehensive index of monitoring effect in target area; S6: Comprehensive judgment of monitoring effect: used to compare the comprehensive index of monitoring effect of the target area with the preset value, and input the comparison result into the interactive feedback step; S7: Interactive feedback: used to import the comparison results into the administrator terminal. When the comparison result of the comprehensive index of the monitoring effect of the target area is lower than the preset value, an alarm will be issued to the administrator's equipment.

2. A wearable monitoring device and working method for medium and large animals according to claim 1, characterized in that: The specific method for obtaining the comprehensive parameters of each sub-area in the sub-area equipment working information collection step is as follows: Comprehensive parameters refer to sub-area body temperature parameters, sub-area heart rate parameters, sub-area respiratory rate parameters, sub-area systolic pressure parameters, sub-area diastolic pressure parameters, sub-area daily drinking water frequency parameters, sub-area environmental temperature parameters, sub-area environmental humidity parameters, sub-area equipment location accuracy parameters, sub-area equipment information storage capacity parameters, sub-area equipment falling off probability parameters, and sub-area equipment failure rate parameters; The sub-region body temperature parameter refers to the body temperature t of the i sub-region i ; The sub-area heart rate parameter refers to the heart rate x of the i sub-area i ; The sub-region respiratory frequency parameter refers to the respiratory frequency H of the sub-region i. i ; The sub-region systolic pressure parameter refers to the systolic pressure of the sub-region i s i ; The sub-region diastolic pressure parameter refers to the diastolic pressure z of the sub-region i. i ; The sub-region daily drinking water frequency parameter refers to the daily drinking water frequency f of the i sub-region i ; The sub-region ambient temperature parameter refers to the i sub-region ambient temperature T i ; The sub-region environmental humidity parameter refers to the i sub-region environmental humidity W i ; The sub-area device location accuracy parameter refers to the i sub-area device location accuracy wzjd i ; The sub-area device information storage capacity parameter refers to the i sub-area device information storage capacity ccl i ; The sub-area device dropout probability parameter refers to the device dropout probability P of the i-th sub-area device. t ; The sub-region equipment failure rate parameter refers to the sub-region equipment failure rate P g .

3. A wearable monitoring device and working method for medium and large animals according to claim 1, characterized in that: The specific method for collecting the daily drinking water frequency parameters of the sub-area is as follows: using GPS to mark the water source near the device, the number of times the animals go to the water source in a single day is counted.

4. A wearable monitoring device and working method for medium and large animals according to claim 1, characterized in that: The mathematical model of the sub-region animal state coefficient is as follows: AM i refers to the animal status coefficient of sub-region i, t i Refers to the body temperature of the sub-region t i , X i Refers to the heart rate of the i sub-area, H i Refers to the respiratory rate of sub-area i, s i refers to the systolic pressure of the i sub-area, z i refers to the diastolic pressure in the i subregion, f i refers to the frequency of drinking water in a single day in sub-area i, and t, s, z, H and X refer to the average body temperature, systolic blood pressure, diastolic blood pressure, respiratory rate and heart rate of the population in a healthy state, respectively.

5. A wearable monitoring device and working method for medium and large animals according to claim 1, characterized in that: The mathematical model of the animal survival environment coefficient of the sub-region is as follows: Among them BM i Refers to the animal survival environment coefficient of sub-region i, T i Refers to the ambient temperature of the i-th sub-area, W i refers to the environmental humidity of sub-region i, T and W refer to the average temperature and humidity of the daily living environment of the population, respectively.

6. A wearable monitoring device and working method for medium and large animals according to claim 1, characterized in that: The mathematical model of the sub-area equipment quality coefficient is as follows: Among them, CM i Refers to the equipment quality coefficient of sub-area i, wzjd i Refers to the device location accuracy of the i sub-area, ccl i Refers to the storage capacity of device information in sub-area i, P t refers to the probability of device failure in sub-area i, P g Refers to the equipment failure rate in the sub-region.

7. A wearable monitoring device and working method for medium and large animals according to claim 1, characterized in that: The mathematical model of the sub-region monitoring effect comprehensive index is as follows: in Refers to the comprehensive index of monitoring effect in the sub-region, AM i Refers to the animal status coefficient of sub-region i, BM i Refers to the animal living environment coefficient of sub-region i, CM i It refers to the equipment quality coefficient of sub-area i, and α1, α2, and α3 refer to weight coefficients.

8. A wearable monitoring device and working method for medium and large animals according to claim 1, characterized in that: The mathematical model of the comprehensive index of monitoring effect of the target area is as follows: in Refers to the comprehensive index of monitoring effect in the target area. Refers to the comprehensive index of sub-region monitoring effect.

9. A wearable monitoring device and working method for medium and large animals according to claim 1, characterized in that: The preset value is a warning value for evaluating the effectiveness of wearable monitoring equipment, the animal living environment, and the physical health of animals based on industry practical experience. When the comprehensive index of the target area monitoring effect is lower than the preset value, it means that the effect of the wearable monitoring equipment in the area is poor, the animal living environment is poor, and the physical health of animals is poor.

10. A wearable monitoring device and working method for medium and large animals according to claim 1, characterized in that: When the comparison result of the interactive feedback step is lower than the preset value, the system will trigger an alarm function on the terminal, send a warning signal to the management personnel through sound, vibration and pop-up window, and give relevant parameters, and use artificial intelligence to help management personnel analyze the reasons affecting the comprehensive index of monitoring effect of the target area.

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