A method of operation for a wearable monitoring device for medium to large animals

Abstract

The application discloses a working method of a wearable monitoring device for medium and large animals, and particularly relates to the field of animal health monitoring, which comprises the following steps: a sub-region division step, a sub-region device working information collection step, a sub-region data standardization processing step, a sub-region monitoring device comprehensive analysis step, a target region monitoring device comprehensive analysis step, a monitoring effect comprehensive judgment step and an interactive feedback step. Through accurate region division, the application comprehensively monitors the target region, collects comprehensive information covering animal state, device performance and environmental data, establishes a mathematical model to comprehensively evaluate the performance of the wearable monitoring device, measures the overall effect of the wearable monitoring device in multiple dimensions, realizes comprehensive evaluation of the operation effect of the wearable monitoring device, and effectively improves the working efficiency and quality of the device. The innovative method provides strong support for field animal monitoring and livestock management.

Description

Technical Field

[0001] This invention relates to the field of animal health monitoring technology, and more specifically, to a method for operating a wearable monitoring device for medium to large animals. Background Technology

[0002] Wildlife monitoring is a crucial component of ecological research, wildlife conservation, and biodiversity assessment. However, the wild environment is complex and ever-changing, and traditional manual monitoring methods are not only time-consuming and labor-intensive but also struggle to provide round-the-clock, comprehensive monitoring of animals. Therefore, developing a wearable monitoring device that is adaptable to the wild environment, stable, reliable, and capable of real-time data transmission is of paramount importance.

[0003] This wearable monitoring device has broad application prospects in wildlife monitoring. It can not only provide rich data support for ecological research, promoting in-depth studies on wildlife behavior, migration patterns, and other aspects; it can also provide a powerful tool for wildlife conservation, helping monitoring personnel to promptly detect and address issues such as illegal hunting and habitat destruction; and simultaneously, it can provide scientific evidence for biodiversity assessment, promoting the sustainable use and protection of natural resources.

[0004] However, in practical use, it still has some drawbacks. For example, the data collected by current technology is too singular, making it difficult to accurately assess the overall condition of the wearable monitoring device. Furthermore, current monitoring of wearable monitoring devices mainly relies on single dimensions, such as GPS location information and animal vital signs, lacking comprehensive indicators. Monitoring based solely on a single dimension ignores the effectiveness of the monitoring device and the impact of the animal's living environment, thus affecting 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, embodiments of the present invention provide a method for operating a wearable monitoring device for medium and large animals, and solve the problems mentioned in the background art through the following solution.

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

[0007] Preferably, step 1: sub-region division: used to mark 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 label them as 1, 2, 3...i in sequence;

[0008] Step 2: Sub-region equipment operation information collection: This includes animal status information collection, equipment information collection, and environmental information collection steps. It 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.

[0009] Step 3: Sub-region data standardization processing: This step standardizes the collected data by performing Z-score standardization to eliminate the influence of dimensions, and then outputs the processed data to the sub-region monitoring equipment for comprehensive analysis.

[0010] Step 4: Comprehensive Analysis of Sub-region Monitoring Equipment: This step involves importing the data processed in the sub-region data standardization step into mathematical models for the sub-region animal state coefficient, sub-region animal survival environment coefficient, sub-region equipment quality coefficient, and sub-region monitoring effect comprehensive index, and calculating these models to obtain the sub-region animal state coefficient, sub-region animal survival environment coefficient, sub-region equipment quality coefficient, and sub-region monitoring effect comprehensive index.

[0011] Step 5: Comprehensive Analysis of Monitoring Equipment in the Target Area: This step involves importing the data obtained from the comprehensive analysis of monitoring equipment in the sub-area into the mathematical model of the comprehensive index of monitoring effectiveness in the target area and performing calculations to obtain the comprehensive index of monitoring effectiveness in the target area.

[0012] Step 6: Comprehensive Judgment of Monitoring Results: This step compares the comprehensive index of the monitoring results of the target area with the preset value and inputs the comparison results into the interactive feedback step.

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

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

[0015] The comprehensive parameters refer to the sub-region body temperature parameters, sub-region heart rate parameters, sub-region respiratory rate parameters, sub-region systolic blood pressure parameters, sub-region diastolic blood pressure parameters, sub-region daily water intake frequency parameters, sub-region ambient temperature parameters, sub-region ambient humidity parameters, sub-region equipment position accuracy parameters, sub-region equipment information storage capacity parameters, sub-region equipment detachment probability parameters, and sub-region equipment failure rate parameters.

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

[0017] The sub-region heart rate parameter refers to the heart rate of sub-region i. ;

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

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

[0020] The subregion diastolic pressure parameter refers to the i-region diastolic pressure. ;

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

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

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

[0024] The sub-region device position accuracy parameter refers to the sub-region device position accuracy. ;

[0025] The sub-region device information storage parameter refers to the sub-region device information storage capacity. ;

[0026] The sub-region equipment detachment probability parameter refers to the detachment probability of equipment in sub-region i. ;

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

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

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

[0030] Preferably, the mathematical model for the animal state coefficients in the sub-region is as follows:

[0031] = ,in The animal state coefficient of subregion i. Body temperature in sub-region , Refers to the heart rate in the i-subregion. Refers to the respiratory rate of subregion i. The contraction pressure of the i-subregion. Diastolic pressure in the i-region refers to the pressure in the i-region. This refers to the daily drinking frequency in sub-region i. , , , , These 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 for the animal survival environment coefficient of the sub-region is as follows:

[0033] = ,in The environmental coefficient for animal survival in sub-region i. Refers to the ambient temperature of sub-region i. Refers to the environmental humidity of sub-region i. , These refer to the average temperature and humidity of the daily living environment of this population, respectively.

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

[0035] = ,in Refers to the equipment quality coefficient of sub-region i. Refers to the positioning accuracy of devices in sub-region i. This refers to the storage capacity of device information in sub-region i. The probability of device detachment in sub-region i. The failure rate of equipment in the sub-region.

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

[0037] = ,in The comprehensive index of monitoring effectiveness in the sub-regions The animal state coefficient of subregion i. The environmental coefficient for animal survival in sub-region i. Refers to the equipment quality coefficient of sub-region i. , , This refers to the weighting coefficient.

[0038] Preferably, the weighting coefficient , , It is obtained through the entropy method, and the specific calculation steps of the entropy method are as follows:

[0039] Data standardization: Since the units of measurement for various indicators may differ, it is necessary to standardize the collected data to eliminate the influence of dimensions. Common standardization methods include Z-score standardization and range standardization.

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

[0041] Calculate information entropy: Based on the definition and calculation formula of information entropy, calculate the information entropy ej of the j-th indicator. The smaller the information entropy, the greater the degree of variation of the indicator, and the greater the amount of information it provides.

[0042] Calculate information entropy redundancy: Information entropy redundancy dj is the complement of information entropy, i.e., dj = 1 - ej. The larger the information entropy redundancy, the more information the indicator contains, and the greater its impact on the overall evaluation.

[0043] Calculate the weights: Based on the information entropy redundancy of each indicator, calculate its weight in the comprehensive evaluation. 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 for the comprehensive index of the target area monitoring effect is as follows:

[0045] = ,in The comprehensive index of the monitoring effect of the target area. The comprehensive index of monitoring effectiveness in the sub-region refers to the overall index of monitoring effectiveness in the sub-region.

[0046] Preferably, the preset value is a warning value obtained based on industry practical experience to evaluate the effectiveness of wearable monitoring devices, animal living environment, and animal health status. When the comprehensive index of the target area monitoring effect is lower than the preset value, it indicates that the effectiveness of the wearable monitoring devices in the area is poor, the animal living environment is poor, and the animal health status is poor, and corresponding measures need to be taken to reduce the risk.

[0047] Preferably, when the comparison result is lower than the preset value, the system will trigger an alarm function on the terminal, and issue a warning signal to the manager through sound, vibration and pop-up window and provide relevant parameters. Artificial intelligence helps the manager analyze the reasons affecting the comprehensive index of the monitoring effect of the target area, and further track down the specific aspects affecting the comprehensive performance, such as poor effect of wearable monitoring equipment, poor animal living environment and poor animal health.

[0048] The technical effects and advantages of this invention are as follows:

[0049] 1. This invention achieves real-time and comprehensive monitoring of the target area through precise area division. By using a sub-area division module, the target area is divided into several sub-areas, and basic information is collected in each sub-area. This basic information includes sub-area body temperature, sub-area heart rate, sub-area respiratory rate, sub-area systolic blood pressure, sub-area diastolic blood pressure, sub-area daily water intake frequency, sub-area ambient temperature, sub-area ambient humidity, sub-area device location accuracy, sub-area device information storage capacity, sub-area device detachment probability, and sub-area device failure rate. This covers three major aspects of the wearable monitoring device: animal status information, device information, and environmental information, thus providing a more comprehensive and detailed monitoring method for the overall performance of the wearable monitoring device.

[0050] 2. Through in-depth analysis of the collected data, this invention establishes a mathematical model that comprehensively assesses the overall performance of the wearable monitoring device. By establishing such a comprehensive model, this invention can better measure the overall effectiveness of the wearable monitoring device from different dimensions. This comprehensive evaluation method can provide a more complete understanding of the overall effectiveness of the wearable monitoring device in actual operation, thereby improving the overall working efficiency and quality of the wearable monitoring device. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the overall structure of the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] As attached Figure 1 The method for operating a wearable monitoring device for medium to large animals includes a sub-region division step, a sub-region device operation information collection step, a sub-region data standardization processing step, a sub-region monitoring device comprehensive analysis step, a target area monitoring device comprehensive analysis step, a monitoring effect comprehensive judgment step, and an interactive feedback step.

[0054] The sub-region division step is used to mark 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 label them as 1, 2, 3...i in sequence;

[0055] The sub-region equipment operation information collection steps include animal status information collection steps, equipment information collection steps, and environmental information collection steps, which are used to collect data from the sub-region to obtain comprehensive parameters and output the comprehensive parameters to the sub-region data standardization processing steps.

[0056] In the preferred embodiment of this application, the specific method for obtaining the comprehensive parameters of each sub-region in the sub-region device working information acquisition step is as follows:

[0057] In this embodiment, it should be specifically explained that the comprehensive parameters refer to the sub-region body temperature parameters, sub-region heart rate parameters, sub-region respiratory rate parameters, sub-region systolic blood pressure parameters, sub-region diastolic blood pressure parameters, sub-region daily water intake frequency parameters, sub-region ambient temperature parameters, sub-region ambient humidity parameters, sub-region equipment position accuracy parameters, sub-region equipment information storage capacity parameters, sub-region equipment detachment probability parameters, and sub-region equipment failure rate parameters.

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

[0059] The sub-region heart rate parameter refers to the heart rate of sub-region i. ;

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

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

[0062] The subregion diastolic pressure parameter refers to the i-region diastolic pressure. ;

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

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

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

[0066] The sub-region device position accuracy parameter refers to the sub-region device position accuracy. ;

[0067] The sub-region device information storage parameter refers to the sub-region device information storage capacity. ;

[0068] The sub-region equipment detachment probability parameter refers to the detachment probability of equipment in sub-region i. ;

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

[0070] It should be specifically noted in this embodiment that the parameters of sub-region body temperature, sub-region heart rate, sub-region respiratory rate, sub-region systolic blood pressure, sub-region diastolic blood pressure, ambient temperature, ambient humidity, sub-region device position accuracy, sub-region device information storage capacity, sub-region device detachment probability, and sub-region device failure rate are all obtained using conventional methods or conventional equipment. For example, ambient temperature and ambient humidity parameters are collected by the built-in sensors of wearable monitoring devices. Therefore, this embodiment does not impose specific limitations.

[0071] In this embodiment, it should be specifically noted that the sub-region device location accuracy parameter specifically refers to the maximum error value between the actual GPS positioning and the displayed positioning of the device;

[0072] In this embodiment, it should be specifically explained that the daily drinking frequency parameter of the sub-region is collected in the following way: by marking water sources near the GPS device, the number of times the animals go to the water source within a day is counted;

[0073] The sub-region data standardization processing step is used to standardize the collected data. By performing Z-score standardization on the collected data, the influence of dimensions is eliminated, and the processed data is output to the sub-region monitoring equipment comprehensive analysis step.

[0074] In this embodiment, it is important to note that Z-score standardization is a commonly used data preprocessing method. It converts the original data into standardized Z-scores by calculating the mean and standard deviation. This method can eliminate differences in magnitude between data points, enabling comparison and comprehensive analysis of data from different magnitudes.

[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 models of the sub-region animal state coefficient, the sub-region animal survival environment coefficient, the sub-region equipment quality coefficient, and the sub-region monitoring effect comprehensive index, and calculate them to obtain the sub-region animal state coefficient, the sub-region animal survival environment coefficient, the sub-region equipment quality coefficient, and the sub-region monitoring effect comprehensive index.

[0076] In this embodiment, it should be specifically explained that the mathematical model for the animal state coefficients of the sub-region is as follows:

[0077] = ,in The animal state coefficient refers to the i-th subregion. Body temperature in sub-region , Refers to the heart rate in the i-subregion. Refers to the respiratory rate of subregion i. The contraction pressure of the i-subregion. The i-region refers to diastolic pressure. This refers to the daily drinking frequency in sub-region i. , , , , These 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] In this embodiment, it should be specifically explained that the mathematical model for the animal survival environment coefficient of the sub-region is as follows:

[0079] = ,in The environmental coefficient for animal survival in sub-region i. Refers to the ambient temperature of sub-region i. Refers to the environmental humidity of sub-region i. , These refer to the average temperature and humidity of the daily living environment of this population, respectively.

[0080] In this embodiment, it should be specifically explained that the mathematical model for the sub-region equipment quality coefficient is as follows:

[0081] = ,in Refers to the equipment quality coefficient of sub-region i. Refers to the positioning accuracy of devices in sub-region i. This refers to the storage capacity of device information in sub-region i. The probability of device detachment in sub-region i. The failure rate of equipment in the sub-area;

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

[0083] = ,in The comprehensive index of monitoring effectiveness in the sub-regions The animal state coefficient refers to the i-th subregion. The environmental coefficient for animal survival in sub-region i. Refers to the equipment quality coefficient of sub-region i. , , Weighting coefficient;

[0084] In this embodiment, it should be specifically noted that the weighting coefficient , , It is obtained through the entropy method, and the specific calculation steps of the entropy method are as follows:

[0085] Data standardization: Since the units of measurement for various indicators may differ, it is necessary to standardize the collected data to eliminate the influence of dimensions. Commonly used standardization methods include Z-score standardization and range standardization.

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

[0087] Calculate information entropy: Based on the definition and calculation formula of information entropy, calculate the information entropy ej of the j-th indicator. The smaller the information entropy, the greater the degree of variation of the indicator, and the greater the amount of information it provides.

[0088] Calculate information entropy redundancy: Information entropy redundancy dj is the complement of information entropy, i.e., dj = 1 - ej. The larger the information entropy redundancy, the more information the indicator contains, and the greater its impact on the overall evaluation.

[0089] Calculate the weights: Based on the information entropy redundancy of each indicator, calculate its weight in the comprehensive evaluation. 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 comprehensive analysis step of the target area monitoring equipment is used to import the data obtained from the comprehensive analysis step of the sub-area monitoring equipment into the mathematical model of the comprehensive index of the target area monitoring effect and calculate it to obtain the comprehensive index of the target area monitoring effect.

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

[0092] = ,in The comprehensive index of the monitoring effect of the target area. The comprehensive index of monitoring effectiveness in the sub-region refers to the overall index of monitoring effectiveness in the sub-region.

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

[0094] In this embodiment, it should be specifically noted that the preset value is a warning value obtained based on industry practical experience to evaluate the effectiveness of wearable monitoring devices, animal living environment, and animal health status. When the comprehensive index of the target area monitoring effect is lower than the preset value, it indicates that the effectiveness of the wearable monitoring device in the area is poor, the animal living environment is poor, and the animal health status is poor, and corresponding measures need to be taken to reduce the risk.

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

[0096] In this embodiment, it should be specifically noted that when the comparison result is lower than the preset value, the system will trigger an alarm function on the terminal, and issue a warning signal to the management personnel through sound, vibration and pop-up window and provide relevant parameters. Artificial intelligence helps the management personnel analyze the reasons affecting the comprehensive index of the monitoring effect of the target area, and further track down the specific aspects affecting the comprehensive performance, such as poor effect of wearable monitoring equipment, poor animal living environment and poor animal health.

[0097] Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other.

[0098] In conclusion, 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 within the protection scope of the present invention.

Claims

1. A method for operating a wearable monitoring device for medium to large animals, characterized in that, include: The steps include: sub-region division, sub-region equipment operation information collection, sub-region data standardization processing, sub-region monitoring equipment comprehensive analysis, target area monitoring equipment comprehensive analysis, monitoring effect comprehensive judgment, and interactive feedback. S1: Sub-region division: Used to define the target monitoring area as the animal population to be monitored, and to divide the target monitoring area into sub-monitoring areas according to different individuals, and to label them sequentially as 1, 2, 3...i; S2: Sub-region equipment operation information collection: This includes animal status information collection steps, equipment information collection steps, and environmental information collection steps. It 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 steps. S3: Sub-region data standardization processing: This is used to standardize the collected data. By performing Z-score standardization on the collected data, the influence of dimensions is eliminated, and the processed data is output to the sub-region monitoring equipment for comprehensive analysis. S4: Comprehensive Analysis of Sub-region Monitoring Equipment: This is used to import the data processed in the sub-region data standardization step into the mathematical models of the sub-region animal status coefficient, the sub-region animal survival environment coefficient, the sub-region equipment quality coefficient, and the sub-region monitoring effect comprehensive index, and calculate them to obtain the sub-region animal status coefficient, the sub-region animal survival environment coefficient, the sub-region equipment quality coefficient, and the sub-region monitoring effect comprehensive index. The mathematical model for the animal state coefficients in the sub-region is as follows: = ,in The animal state coefficient refers to the i-th subregion. Body temperature in sub-region , Refers to the heart rate in the i-subregion. Refers to the respiratory rate of subregion i. The contraction pressure of the i-subregion. Diastolic pressure in the i-region refers to the pressure in the i-region. This refers to the daily drinking frequency in sub-region i. , , , as well as These 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. The mathematical model for the animal survival environment coefficient in the sub-region is as follows: = ,in The environmental coefficient for animal survival in sub-region i. Refers to the ambient temperature of sub-region i. Refers to the environmental humidity of sub-region i. , These refer to the average temperature and humidity of the daily living environment of this population, respectively. The mathematical model for the sub-region equipment quality coefficient is as follows: = ,in Refers to the equipment quality coefficient of sub-region i. Refers to the positioning accuracy of devices in sub-region i. This refers to the storage capacity of device information in sub-region i. The probability of device detachment in sub-region i. The failure rate of equipment in the sub-area; The mathematical model for the comprehensive index of the monitoring effect of the sub-region is as follows: = ,in The comprehensive index of monitoring effectiveness in the sub-regions The animal state coefficient refers to the i-th subregion. The environmental coefficient for animal survival in sub-region i. Refers to the equipment quality coefficient of sub-region i. , , Weighting coefficient; S5: Comprehensive Analysis of Monitoring Equipment in Target Area: This step imports the data obtained from the comprehensive analysis of monitoring equipment in sub-areas into the mathematical model of the comprehensive index of monitoring effect in target area and performs calculations to obtain the comprehensive index of monitoring effect in target area. The mathematical model for the comprehensive index of the monitoring effect of the target area is as follows: = ,in The comprehensive index of the monitoring effect of the target area. The comprehensive index of monitoring effectiveness in the sub-region; S6: Comprehensive Judgment of Monitoring Results: This is used to compare the comprehensive index of the monitoring results of the target area with the preset value and input the comparison results into the interactive feedback step. S7: Interactive Feedback: Used to import comparison results into the administrator terminal. When the comprehensive index comparison result of the target area monitoring effect is lower than the preset value, an alarm will be issued to the administrator's device.

2. The working method of a wearable monitoring device for medium to large animals according to claim 1, characterized in that: The specific method for obtaining the comprehensive parameters of each sub-region in the sub-region equipment operation information collection step is as follows: The comprehensive parameters refer to the sub-region body temperature parameters, sub-region heart rate parameters, sub-region respiratory rate parameters, sub-region systolic blood pressure parameters, sub-region diastolic blood pressure parameters, sub-region daily water intake frequency parameters, sub-region ambient temperature parameters, sub-region ambient humidity parameters, sub-region equipment position accuracy parameters, sub-region equipment information storage capacity parameters, sub-region equipment detachment probability parameters, and sub-region equipment failure rate parameters. The sub-region body temperature parameter refers to the body temperature of sub-region i. ; The sub-region heart rate parameter refers to the heart rate of sub-region i. ; The sub-region respiratory rate parameter refers to the respiratory rate of sub-region i. ; The sub-region systolic pressure parameter refers to the i-region systolic pressure. ; The subregion diastolic pressure parameter refers to the i-region diastolic pressure. ; The sub-region daily drinking water frequency parameter refers to the i-region daily drinking water frequency. ; The sub-region ambient temperature parameter refers to the i-region ambient temperature. ; The sub-region environmental humidity parameter refers to the environmental humidity of sub-region i. ; The sub-region device position accuracy parameter refers to the sub-region device position accuracy. ; The sub-region device information storage parameter refers to the sub-region device information storage capacity. ; The sub-region equipment detachment probability parameter refers to the detachment probability of equipment in sub-region i. ; The sub-region equipment failure rate parameter refers to the sub-region equipment failure rate. .

3. The method of operating a wearable monitoring device for medium to large animals according to claim 2, characterized in that: The specific method for collecting the daily drinking frequency parameters of the sub-region is as follows: by using GPS to mark water sources near the equipment, the number of times animals go to the water source within a single day is counted.

4. The method of operating a wearable monitoring device for medium to large animals according to claim 1, characterized in that: The preset value is a warning value obtained based on industry practice experience to evaluate the effectiveness of wearable monitoring equipment, animal living environment, and animal health status. When the comprehensive index of the monitoring effect of the target area is lower than the preset value, it indicates that the effect of the wearable monitoring equipment in the area is poor, the animal living environment is poor, and the animal health status is poor.

5. The method of operating a wearable monitoring device for medium to large animals according to claim 1, characterized in that: When the comparison result is lower than the preset value, the system will trigger an alarm function on the terminal, sending a warning signal to the manager through sound, vibration and pop-up window and providing relevant parameters. Artificial intelligence will help the manager analyze the reasons affecting the comprehensive index of the monitoring effect of the target area.

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