Livestock inspection system and method

Abstract

The invention discloses a livestock inspection system and method, and relates to the technical field of livestock inspection, and the system comprises an inspection scene collection module, an inspection analysis module, an abnormity analysis module and an early warning execution module. An existing animal husbandry inspection system can automatically and accurately conduct inspection work, discover abnormities in time and conduct corresponding processing. However, some problems still exist in the prior art. In order to solve the problem that detection results are not accurate enough due to the fact that detection of livestock abnormity only depends on limited data types such as single physiological parameters, livestock abnormity conditions are obtained through analysis of an inspection analysis module and an abnormity analysis module, and an early warning execution module processes the livestock abnormity conditions; according to the livestock farm management system, the automation and intelligence level of livestock farm management is improved, errors and omissions of manual operation are reduced, the health and production efficiency of livestock and poultry can be effectively guaranteed, and finally the operation benefits and the sustainable development capacity of the livestock farm are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of animal husbandry inspection, and in particular to a animal husbandry inspection system and method. Background Art

[0002] There is a livestock inspection system that integrates multiple sensor technologies and intelligent analysis algorithms. It can perform inspections automatically and accurately, detect abnormalities in a timely manner and take corresponding measures. It has become a key technical requirement for improving the management level of farms. However, there are still some problems in the existing technology. The detection of livestock abnormalities only relies on limited data types, such as a single physiological parameter, resulting in inaccurate detection results. The inspection system often lacks the ability to respond flexibly to different environments and situations. The inspection equipment is not fully utilized, resulting in idling equipment or insufficient inspections. Summary of the invention

[0003] The purpose of the present invention is to solve the problems raised by the above-mentioned background technology and to provide a livestock inspection system and method.

[0004] The purpose of the present invention can be achieved by the following technical solutions:

[0005] In a first aspect, the present invention provides a livestock inspection system, including an inspection analysis module, an abnormality analysis module and an early warning execution module;

[0006] The inspection analysis module is used to analyze the inspection data corresponding to the breeding area QUN. The specific process is: analyzing the meteorological data corresponding to the breeding area QUN to obtain the temperature and humidity values, and comparing the temperature and humidity values ​​with the temperature and humidity thresholds in the corresponding breeding area QUN to obtain the meteorological warning signal; analyzing the inspection scene of the breeding area QUN to select the corresponding livestock inspection equipment, including: analyzing the environmental monitoring data of the corresponding breeding area QUN to obtain the available space volume; analyzing the breeding density of the breeding area QUN to obtain the number of inspections;

[0007] The abnormal analysis module performs inspection abnormality analysis on the livestock inspection equipment, and the specific process is as follows:

[0008] Analyze the livestock physiological data to generate corresponding livestock abnormal body temperature signals, corresponding livestock abnormal heart rate signals, corresponding livestock abnormal respiratory rate signals and their corresponding signal strengths; then output the physiological value SLZ through the formula SLZ=μ×b1+θ×b2+ρ×b3, where μ is the corresponding livestock abnormal body temperature signal strength, θ is the corresponding livestock abnormal heart rate signal strength, and ρ is the corresponding livestock normal respiratory rate abnormal signal strength; b1, b2 and b3 are all preset signal strength weight factors, and the physiological value SLZ is compared with the preset strength threshold to obtain the strength coefficient;

[0009] Analyzing the behavior data to obtain a behavior value, and comparing the behavior value with a preset behavior threshold to generate a corresponding livestock behavior abnormality signal;

[0010] The warning execution module shown is used to obtain the signals generated by the inspection analysis module and the abnormality analysis module to perform inspections, alarms and commands.

[0011] As a preferred embodiment of the present invention, it also includes an inspection scene acquisition module, which is used to obtain inspection data of different livestock breeding areas, the inspection data including livestock physiological data, environmental monitoring data, behavioral data and meteorological data, and distinguish the inspection data of different breeding areas, and mark the different breeding areas as QUN, N = 1, 2, 3, ..., m, m represents the total number of breeding areas.

[0012] As a preferred embodiment of the present invention, the specific process of analyzing the meteorological data corresponding to the breeding area QUN to obtain the temperature and humidity values ​​is:

[0013] Obtain the meteorological data corresponding to the breeding area QUN, collect the temperature and humidity in the weather forecast, substitute them into the curve to obtain the temperature and humidity monitoring curve, set the WS interval in the graph, obtain the maximum and minimum temperature and humidity maximum and minimum values ​​​​and the absolute slope in the WS interval, and then output the temperature and humidity value WSZ through the formula WSZ = (ΔW×a1)2+ΔS×a2+|XW+XS|×a3, ΔW is the absolute temperature difference of the WS interval, ΔS is the absolute temperature difference of the WS interval, X W is the slope between the maximum and minimum temperature in the WS interval, X S is the slope between the maximum and minimum temperature in the WS interval, and a1, a2, and a3 are all preset weight factors; the temperature and humidity value WSZ is compared with the temperature and humidity threshold in the corresponding breeding area QUN. If the temperature and humidity value WSZ is greater than the temperature and humidity threshold in the corresponding breeding area QUN, a meteorological warning signal is generated; if the meteorological data obtained is a meteorological disaster, a meteorological warning signal is generated.

[0014] As a preferred embodiment of the present invention, the specific process of analyzing the QUN environmental monitoring data of the corresponding breeding area to obtain the available space volume is:

[0015] The environmental monitoring data include breeding facilities and breeding quantity. The breeding facilities in the corresponding breeding area are analyzed. If the livestock house is closed, the internal height, width and length of the livestock house are obtained, and the internal space volume of the livestock house is calculated. The space volume occupied by the drinking water system, feeding equipment, lighting facilities and sewage facilities in the livestock house is then removed to obtain the available space volume.

[0016] As a preferred embodiment of the present invention, the specific process of analyzing the breeding density of the breeding area QUN to obtain the number of inspections is:

[0017] Get the breeding area of ​​the livestock house, and calculate the breeding density with the breeding quantity of the breeding area QUN, and match the obtained breeding density with the corresponding preset breeding area QUN density interval. If the breeding density belongs to UN density interval one, it is matched with inspection frequency factor one; if the breeding density belongs to UN density interval two, it is matched with inspection frequency factor two; if the breeding density belongs to UN density interval three, it is matched with inspection frequency factor three; if the breeding density belongs to UN density interval four, it is matched with inspection frequency factor four; and so on; the inspection frequency factor is the number of inspections of different breeding areas QUN within a period of time, and the number of inspections within a period of time does not exceed the preset number threshold.

[0018] As a preferred embodiment of the present invention, the specific process of analyzing the livestock physiological data is as follows:

[0019] The physiological data of QUN in different breeding areas is obtained by the livestock inspection equipment, and then the infrared thermal imaging camera carried by the livestock inspection equipment is used to obtain the physiological data. The obtained livestock infrared image is assigned a value according to the corresponding RGB, and the livestock infrared image R value is matched with the corresponding R value preset weight, the livestock infrared image G value is matched with the corresponding G value preset weight, and the livestock infrared image B value is matched with the corresponding B value preset weight to obtain the corresponding livestock body temperature RGB, and then the corresponding livestock body temperature RGB and the corresponding livestock normal range are matched with the preset body temperature stored in the database to obtain the livestock body temperature and the livestock normal body temperature range. If the livestock body temperature does not belong to the livestock normal body temperature range, a corresponding livestock body temperature abnormality signal is generated, and then the difference between the livestock body temperature and the middle value of the livestock normal body temperature range is calculated, and the strength of the corresponding livestock body temperature abnormality signal is determined according to the difference.

[0020] The optical scanner carried by the livestock inspection equipment is used to obtain the heart rate of the livestock. The scanner emits light of a specific wavelength, which penetrates the skin and is absorbed or reflected by the blood. The sensor in the scanner then receives the reflected light signal, and then calculates the period of the reflected light signal to obtain the heart rate of the corresponding livestock. Similarly, the normal heart rate range of the corresponding livestock is obtained from the database. If the heart rate of the livestock does not belong to the normal heart rate range of the livestock, a normal heart rate abnormal signal of the corresponding livestock is generated, and then the strength of the abnormal heart rate signal of the corresponding livestock is calculated.

[0021] A thermal imaging camera is used to detect changes in temperature around the nostrils or mouth during breathing, and the number of breathing changes in one cycle is recorded, and the number of breathing changes in one cycle is used as the corresponding livestock breathing frequency; the corresponding livestock normal breathing frequency range is obtained from the database. If the livestock heart rate does not belong to the livestock normal breathing frequency range, the corresponding livestock normal breathing frequency abnormal signal is generated. Similarly, the corresponding livestock breathing frequency abnormal signal intensity is obtained.

[0022] As a preferred embodiment of the present invention, the specific process of comparing the physiological value SLZ with the preset intensity threshold to obtain the intensity coefficient is:

[0023] If the physiological value SLZ is greater than the preset intensity threshold, the corresponding livestock body temperature abnormal signal intensity, the corresponding livestock normal heart rate abnormal signal intensity and the corresponding livestock normal respiratory rate abnormal signal intensity are multiplied by the corresponding preset signal strength weight factors to obtain the intensity coefficients, and the sizes are compared. If the corresponding intensity coefficient of the livestock body temperature abnormal signal intensity is the maximum value, the corresponding livestock body temperature abnormal signal is generated, and so on, the corresponding livestock heart rate abnormal signal and the corresponding livestock respiratory rate abnormal signal are generated.

[0024] In a second aspect, the present invention provides a livestock inspection method, the method comprising:

[0025] S1: Obtain inspection data from different breeding areas QUN through livestock inspection equipment;

[0026] S2: Analyze the inspection data and meteorological data of the breeding area QUN to obtain the available space volume and inspection frequency;

[0027] S3: Perform abnormal analysis on the inspection data of QUN in different breeding areas through livestock inspection equipment to generate livestock abnormal temperature signals, heart rate abnormal signals, respiratory frequency abnormal signals and corresponding abnormal signal strengths and generate corresponding abnormal behavior signals;

[0028] S4: Take appropriate actions based on the signal generated in S3.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. The present invention integrates a variety of advanced technologies to achieve comprehensive and accurate monitoring and analysis of different breeding areas; the system can dynamically adjust the inspection frequency and method according to environmental monitoring data, breeding density and meteorological conditions to ensure timely discovery and early warning of potential risks; it improves the automation and intelligence level of livestock farm management, reduces errors and omissions in manual operations, and can effectively protect the health and production efficiency of livestock and poultry, ultimately improving the operational benefits and sustainable development capabilities of the farm.

[0031] 2. The present invention uses advanced sensor technology and image processing algorithms through the abnormal analysis module to comprehensively monitor and analyze the physiological data and behavioral data of livestock, and can timely discover and warn of potential health problems or behavioral abnormalities; through automated detection and analysis of body temperature, heart rate, respiratory rate and behavioral traces, the system can quickly identify abnormal situations and classify them, greatly improving the accuracy and efficiency of inspections and reducing the need for manual intervention; the precise and efficient abnormal analysis mechanism can not only significantly improve the level of intelligent animal husbandry management, but also effectively ensure the health and safety of livestock and poultry, reduce breeding risks and improve overall production efficiency.

[0032] 3. The present invention realizes flexible and intelligent inspection and early warning functions by accurately acquiring and processing abnormal signals; the system can automatically select appropriate inspection equipment, such as drones or other equipment, according to real-time meteorological conditions and the characteristics of the breeding area, to focus on monitoring livestock suspected of abnormalities, ensuring that problems are discovered and handled in a timely manner; when an abnormality is confirmed, the system immediately issues an alarm and notifies relevant personnel, responds quickly, and reduces losses; it greatly improves inspection efficiency and response capabilities, ensuring that farms can maintain a high level of health monitoring and management under various conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0034] Figure 1 It is a principle block diagram of the present invention;

[0035] Figure 2 It is a diagram of the method steps of the present invention;

[0036] Figure 3 It is the temperature and humidity monitoring curve diagram of the present invention. DETAILED DESCRIPTION

[0037] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. 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.

[0038] It should be understood that the terms "include" and "comprising" used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0039] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and claims, the singular forms of "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and claims refers to any combination of one or more of the associated listed items and all possible combinations, including these combinations.

[0040] Example 1: Please refer to Figure 1 As shown, the present application provides a livestock inspection system on one hand, including an inspection scene acquisition module, an inspection analysis module, an abnormality analysis module and an early warning execution module;

[0041] The inspection scene acquisition module is used to obtain inspection data of different livestock breeding areas, including livestock physiological data, environmental monitoring data, behavioral data and meteorological data, etc.; and the inspection data of different breeding areas are distinguished, and different breeding areas are marked as QUN, N = 1, 2, 3, ..., m; the inspection scene acquisition module is used to obtain inspection data of different livestock breeding areas, which is obtained through livestock inspection equipment, and its livestock inspection equipment includes drones, fixed monitoring cameras, biosensors, biometric identification equipment and rail-based integrated inspection equipment, etc.;

[0042] The inspection analysis module analyzes the inspection data corresponding to the QUN in the breeding area. The specific process is as follows:

[0043] See also Figure 3 As shown in the figure, by analyzing the meteorological data corresponding to the breeding area QUN, the meteorological data includes temperature, humidity, precipitation, wind speed and direction, and meteorological disasters; and by collecting the temperature and humidity of the weather forecast, substituting them into the curve chart to obtain the temperature and humidity monitoring curve chart, and setting the WS interval in the chart to obtain the maximum temperature, minimum temperature and maximum humidity, minimum humidity and absolute slope in the WS interval, and then output the temperature and humidity value WSZ through the formula WSZ = (ΔW×a1)2+ΔS×a2+|XW+XS|×a3, ΔW is the absolute temperature difference of the WS interval, ΔS is the absolute temperature difference of the WS interval, X W is the slope between the maximum and minimum temperature in the WS interval, X Sis the slope between the maximum and minimum temperature in the WS interval, a1, a2, and a3 are all preset weight factors, and their sizes are custom settings, such as 1.3, 1.6, and 1.4 respectively; the temperature and humidity value WSZ is compared with the temperature and humidity threshold in the corresponding breeding area QUN. If the temperature and humidity value WSZ is greater than the temperature and humidity threshold in the corresponding breeding area QUN, a meteorological warning signal is generated; if the meteorological data obtained is a meteorological disaster, a meteorological warning signal is generated; when a meteorological warning signal is generated, the livestock inspection equipment will conduct an inspection;

[0044] Then, by analyzing the inspection scene of QUN in the breeding area, the corresponding livestock inspection equipment is selected. The specific process is as follows:

[0045] Obtain the QUN environmental monitoring data of the corresponding breeding area for analysis. The environmental monitoring data includes breeding facilities and breeding quantity, wherein the breeding facilities include livestock houses, drinking water systems, feeding equipment, lighting facilities and sewage treatment facilities, etc.; and according to the QUN breeding facilities of the corresponding breeding area, if the livestock house (livestock houses include closed, semi-closed and open types) is closed, obtain the internal height, width and length of the livestock house, and calculate the internal space volume of the livestock house, and then remove the space volume occupied by the drinking water system, feeding equipment, lighting facilities and sewage treatment facilities in the livestock house to obtain the available space volume;

[0046] Further, the breeding density of the breeding area QUN is analyzed to obtain the breeding area of ​​the livestock house, and the breeding density is calculated based on the breeding number of QUN in the breeding area, and the obtained breeding density is matched with the corresponding preset breeding area QUN density interval, which includes QUN density interval one, QUN density interval two, QUN density interval three and QUN density interval four; if the breeding density belongs to UN density interval one, it is matched with inspection number factor one; if the breeding density belongs to UN density interval two, it is matched with inspection number factor two; if the breeding density belongs to UN density interval three, it is matched with inspection number factor three; if the breeding density belongs to UN density interval four, it is matched with inspection number factor four; and so on; it should be noted that the inspection number factor is the number of inspections of QUN in different breeding areas within a period of time, and the number of inspections within a period of time does not exceed the preset number threshold;

[0047] The abnormal analysis module uses livestock inspection equipment to perform inspection abnormality analysis. The specific process is as follows:

[0048] Inspections are conducted in different breeding areas. If the breeding area is open or open-air, it is monitored by biosensors and surveillance cameras. If the breeding area is indoor or semi-enclosed, it is inspected by biosensors, biometric identification equipment and rail-mounted integrated inspection equipment.

[0049] Analyze the physiological data of livestock, and obtain the physiological data of QUN in different breeding areas through livestock inspection equipment; livestock physiological data include body temperature, heart rate and respiratory rate, etc. The track integrated inspection equipment obtains the body temperature of livestock, and the infrared thermal imaging camera carried by the livestock inspection equipment obtains it, and the obtained livestock infrared image is assigned according to the corresponding RGB, and then the livestock infrared image R value is matched with the corresponding R value preset weight, and the livestock infrared image G value is matched with the corresponding G value preset weight, then the livestock infrared image B The value is matched with the corresponding B value preset weight to obtain the corresponding livestock body temperature RGB, and then the corresponding livestock body temperature RGB and the corresponding livestock normal interval are matched with the preset body temperature stored in the database to obtain the livestock body temperature and the livestock normal body temperature interval. If the livestock body temperature does not belong to the livestock normal body temperature interval, the corresponding livestock body temperature abnormal signal is generated, and the difference between the livestock body temperature and the middle value of the livestock normal body temperature interval is calculated, and the corresponding livestock body temperature abnormal signal strength is determined according to the difference (the larger the difference, the stronger the corresponding livestock body temperature abnormal signal strength);

[0050] Furthermore, the livestock inspection equipment acquires the heart rate of the livestock, which is acquired by the optical scanner carried by the livestock inspection equipment. The scanner emits light of a specific wavelength (usually infrared or near-infrared), which penetrates the skin and is absorbed or reflected by the blood, and then the sensor in the scanner receives the reflected light signal. With each beat of the heart, the amount of blood changes, resulting in changes in the reflected light signal; these light signals are then acquired periodically to obtain the heart rate of the corresponding livestock; similarly, the normal heart rate range of the corresponding livestock is acquired from the database, and if the livestock heart rate does not belong to the normal heart rate range of the livestock, a corresponding normal heart rate abnormal signal of the livestock is generated, and the difference between the normal heart rate of the livestock and the middle value of the normal heart rate range of the livestock is calculated, and the strength of the abnormal signal of the corresponding normal heart rate of the livestock is determined according to the size of the difference (the larger the difference, the stronger the strength of the abnormal signal of the corresponding normal heart rate of the livestock);

[0051] Furthermore, the livestock inspection equipment or the livestock respiratory frequency is acquired by the infrared thermal imaging camera carried by the livestock inspection equipment, and the thermal imaging camera is used to detect the change of the temperature around the nostrils or the mouth during breathing, and the number of respiratory changes in one cycle is recorded, and the number of respiratory changes in one cycle is used as the corresponding livestock respiratory frequency; similarly, the corresponding livestock normal respiratory frequency interval is obtained from the database, and if the livestock heart rate does not belong to the livestock normal respiratory frequency interval, then the corresponding livestock normal respiratory frequency abnormal signal is generated, and the difference between the livestock normal heart rate and the middle value of the livestock normal respiratory frequency interval is calculated, and the corresponding livestock respiratory frequency abnormal signal strength is determined according to the difference (the larger the difference, the stronger the corresponding livestock normal respiratory frequency abnormal signal strength);

[0052] Then, the physiological value SLZ is output through the formula SLZ=μ×b1+θ×b2+ρ×b3, where μ is the signal strength of the abnormal body temperature of the corresponding livestock, θ is the signal strength of the abnormal heart rate of the corresponding livestock, and ρ is the signal strength of the abnormal normal breathing rate of the corresponding livestock; b1, b2 and b3 are all preset signal strength weight factors, and their sizes are custom settings; the physiological value SLZ is compared with the preset strength threshold. If the physiological value SLZ is greater than the preset strength threshold, the corresponding livestock body temperature abnormal signal strength, the corresponding livestock normal heart rate abnormal signal strength and the corresponding livestock normal breathing rate abnormal signal strength are respectively multiplied by the corresponding preset signal strength weight factors to obtain the strength coefficients, and the sizes are compared. If the corresponding strength coefficient of the livestock body temperature abnormal signal strength is the maximum value, the corresponding livestock body temperature abnormal signal is generated, and so on, the corresponding livestock heart rate abnormal signal and the corresponding livestock breathing rate abnormal signal are generated;

[0053] Analyze behavioral data, including signs of bites, kicks, and other attacks between livestock; obtain signs of bites, kicks, and other attacks by livestock inspection equipment equipped with high-definition cameras; then use image segmentation algorithms (such as U-Net and MaskR-CNN) to detect scar areas on the skin or hair of livestock using the collected high-definition images; perform color and texture analysis on the detected scar areas, and similarly, assign RGB values ​​to the colors of the scar areas to obtain the corresponding livestock color values; match the texture of the scar area with the preset textures stored in the database To texture similarity, the preset textures include bite texture, scratch texture, kick texture, damaged texture, blood texture and bruise texture, etc., obtain the texture similarity corresponding to all textures in the preset texture, and then effectively distinguish the corresponding texture similarity, then compare the corresponding texture similarity with the preset similarity threshold, when the corresponding texture similarity is greater than the preset similarity threshold, it is an effective texture similarity; otherwise, it is invalid; then the corresponding effective texture similarity obtained is weightedly calculated with the corresponding preset texture weight factor to obtain the corresponding livestock texture value; then the formula is used to calculate the corresponding livestock texture value. Output the behavior value XWZ, ys is the corresponding livestock color value, wl is the corresponding livestock texture value, e is a natural number, b4 and b5 are both preset signal strength weight factors, and their sizes are custom settings; compare the behavior value XWZ with the preset behavior threshold, if the behavior value XWZ is greater than the preset behavior threshold, then generate the corresponding livestock behavior abnormal signal;

[0054] The warning execution module shown is used to obtain the signals generated by the inspection analysis module and the abnormal analysis module to perform inspections, alarms and commands, specifically:

[0055] When receiving the corresponding livestock abnormal signal (the corresponding livestock abnormal signal includes the corresponding livestock body temperature abnormal signal, the corresponding livestock normal heart rate abnormal signal and the corresponding livestock normal breathing rate abnormal signal), the wind speed in the real-time meteorological data is obtained. If the wind speed is less than the drone wind speed threshold, and the breeding area QUN is an open or open-air area or a semi-enclosed area, the drone is moved to the area where the corresponding livestock abnormal signal is generated to monitor a certain livestock for a long time. The monitoring time is controlled according to the strength of the corresponding livestock abnormal signal; if the wind speed in the real-time meteorological data is obtained, the wind speed is less than the drone wind speed threshold, and the breeding area QUN is a closed area, the available space volume is used. If the available space volume If the wind speed is greater than the volume of the drone's operating space, the drone will be moved to the area where the corresponding livestock abnormal signal is generated to monitor a certain livestock for a long time. The monitoring time is controlled according to the strength of the corresponding livestock abnormal signal. If the wind speed in the real-time meteorological data is obtained, and the wind speed is greater than the drone wind speed threshold, and the breeding area QUN is a closed area, the available space volume will be used. If the available space volume is less than the drone's operating space volume, long-term monitoring will be carried out through other inspection equipment. If it is determined to be abnormal after monitoring, an alarm will be issued and the corresponding relevant staff will be notified to handle it. When the corresponding livestock behavior abnormal signal is received, an alarm will be directly issued and the corresponding relevant staff will be notified to handle it.

[0056] Example 2: Please refer to Figure 2 As shown, the present application provides a livestock inspection method on the other hand, the specific steps are:

[0057] S1: Obtain inspection data from different breeding areas QUN (N=1, 2, 3, ..., m) through livestock inspection equipment (including drones, fixed surveillance cameras, biosensors, biometric equipment, and rail-based integrated inspection equipment, etc.);

[0058] S2: Analyze the inspection data of QUN in the breeding area:

[0059] Analysis of meteorological data: Analyze the meteorological data corresponding to the breeding area QUN, and calculate the temperature and humidity value WSZ according to the temperature and humidity monitoring curve; if WSZ exceeds the temperature and humidity threshold in the corresponding QUN, or the meteorological data shows that there is a meteorological disaster, a meteorological warning signal is generated, and the livestock inspection equipment is started for inspection;

[0060] Analysis of environmental monitoring data: Analyze the breeding facilities and breeding quantity of the breeding area QUN, calculate the available space volume and breeding density of the livestock house, match it with the preset breeding density range, and determine the appropriate inspection frequency;

[0061] S3: Perform abnormal analysis on the inspection data of QUN in different breeding areas through livestock inspection equipment:

[0062] Physiological data analysis: Analyze the physiological data of livestock such as body temperature, heart rate and respiratory rate, generate abnormal body temperature signal, abnormal heart rate signal and abnormal respiratory rate signal of livestock, and determine the physiological value SLZ according to the signal strength. If SLZ exceeds the preset strength threshold, further analyze the strength of the generated abnormal signal;

[0063] Analysis of behavioral data: Use image segmentation algorithms to analyze behavioral traces such as biting, kicking, and hitting between livestock, and calculate the behavior value XWZ. If XWZ exceeds the preset behavior threshold, a corresponding behavior abnormality signal is generated;

[0064] S4: taking corresponding actions according to the signals generated by the inspection analysis module and the abnormality analysis module.

[0065] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A livestock inspection system, comprising an inspection analysis module, an abnormality analysis module and an early warning execution module, characterized in that: The inspection analysis module is used to analyze the inspection data corresponding to the breeding area QUN. The specific process is: analyzing the meteorological data corresponding to the breeding area QUN to obtain the temperature and humidity value, and comparing the temperature and humidity value with the temperature and humidity threshold value in the corresponding breeding area QUN to obtain a meteorological warning signal; Analyze the inspection scene of the breeding area QUN and select the corresponding livestock inspection equipment, including: analyze the environmental monitoring data of the breeding area QUN to obtain the available space volume; analyze the breeding density of the breeding area QUN to obtain the number of inspections; The abnormal analysis module performs inspection abnormality analysis on the livestock inspection equipment, and the specific process is as follows: Analyze the livestock physiological data to generate corresponding livestock abnormal body temperature signals, corresponding livestock abnormal heart rate signals, corresponding livestock abnormal respiratory rate signals and their corresponding signal strengths; then output the physiological value SLZ through the formula SLZ=μ×b1+θ×b2+ρ×b3, where μ is the corresponding livestock abnormal body temperature signal strength, θ is the corresponding livestock abnormal heart rate signal strength, and ρ is the corresponding livestock normal respiratory rate abnormal signal strength; b1, b2 and b3 are all preset signal strength weight factors, and the physiological value SLZ is compared with the preset strength threshold to obtain the strength coefficient; Analyzing the behavior data to obtain a behavior value, and comparing the behavior value with a preset behavior threshold to generate a corresponding livestock behavior abnormality signal; The warning execution module shown is used to obtain the signals generated by the inspection analysis module and the abnormality analysis module to perform inspections, alarms and commands.

2. A livestock inspection system according to claim 1, characterized in that: It also includes an inspection scene collection module, which is used to obtain inspection data of different livestock breeding areas, the inspection data including livestock physiological data, environmental monitoring data, behavioral data and meteorological data, and distinguish the inspection data of different breeding areas, and mark different breeding areas as QUN, N = 1, 2, 3, ..., m, m represents the total number of breeding areas.

3. A livestock inspection system according to claim 1, characterized in that: The specific process of analyzing the meteorological data corresponding to the breeding area QUN to obtain the temperature and humidity values ​​is as follows: Obtain the meteorological data corresponding to the breeding area QUN, collect the temperature and humidity in the weather forecast, substitute them into the curve to obtain the temperature and humidity monitoring curve, set the WS interval in the graph, obtain the maximum and minimum values ​​of temperature and humidity in the WS interval, and the absolute slope in the WS interval, and then use the formula WSZ = (ΔW×a1) 2 +ΔS×a2+|X W +X S |×a3 outputs the temperature and humidity value WSZ, ΔW is the absolute temperature difference in the WS interval, ΔS is the absolute temperature difference in the WS interval, X W is the slope between the maximum and minimum temperature in the WS interval, X S is the slope between the maximum and minimum temperature in the WS interval, and a1, a2, and a3 are all preset weight factors; the temperature and humidity value WSZ is compared with the temperature and humidity threshold in the corresponding breeding area QUN. If the temperature and humidity value WSZ is greater than the temperature and humidity threshold in the corresponding breeding area QUN, a meteorological warning signal is generated; if the meteorological data obtained is a meteorological disaster, a meteorological warning signal is generated.

4. A livestock inspection system according to claim 3, characterized in that: The specific process of analyzing the QUN environmental monitoring data of the corresponding breeding area to obtain the available space volume is: The environmental monitoring data include breeding facilities and breeding quantity. The breeding facilities in the corresponding breeding area are analyzed. If the livestock house is closed, the internal height, width and length of the livestock house are obtained, and the internal space volume of the livestock house is calculated. The space volume occupied by the drinking water system, feeding equipment, lighting facilities and sewage facilities in the livestock house is then removed to obtain the available space volume.

5. A livestock inspection system according to claim 4, characterized in that: The specific process of analyzing the breeding density of the breeding area QUN to obtain the number of inspections is as follows: Get the breeding area of ​​the livestock house, and calculate the breeding density with the breeding quantity of the breeding area QUN, and match the obtained breeding density with the corresponding preset breeding area QUN density interval. If the breeding density belongs to UN density interval one, it is matched with inspection frequency factor one; if the breeding density belongs to UN density interval two, it is matched with inspection frequency factor two; if the breeding density belongs to UN density interval three, it is matched with inspection frequency factor three; if the breeding density belongs to UN density interval four, it is matched with inspection frequency factor four; and so on; the inspection frequency factor is the number of inspections of different breeding areas QUN within a period of time, and the number of inspections within a period of time does not exceed the preset number threshold.

6. A livestock inspection system according to claim 1, characterized in that: The specific process of analyzing the livestock physiological data is as follows: The physiological data of QUN in different breeding areas is obtained by the livestock inspection equipment, and then the infrared thermal imaging camera carried by the livestock inspection equipment is used to obtain the physiological data. The obtained livestock infrared image is assigned a value according to the corresponding RGB, and the livestock infrared image R value is matched with the corresponding R value preset weight, the livestock infrared image G value is matched with the corresponding G value preset weight, and the livestock infrared image B value is matched with the corresponding B value preset weight to obtain the corresponding livestock body temperature RGB, and then the corresponding livestock body temperature RGB and the corresponding livestock normal range are matched with the preset body temperature stored in the database to obtain the livestock body temperature and the livestock normal body temperature range. If the livestock body temperature does not belong to the livestock normal body temperature range, a corresponding livestock body temperature abnormality signal is generated, and then the difference between the livestock body temperature and the middle value of the livestock normal body temperature range is calculated, and the strength of the corresponding livestock body temperature abnormality signal is determined according to the difference. The optical scanner carried by the livestock inspection equipment is used to obtain the heart rate of the livestock. The scanner emits light of a specific wavelength, which penetrates the skin and is absorbed or reflected by the blood. The sensor in the scanner then receives the reflected light signal, and then calculates the period of the reflected light signal to obtain the heart rate of the corresponding livestock. Similarly, the normal heart rate range of the corresponding livestock is obtained from the database. If the heart rate of the livestock does not belong to the normal heart rate range of the livestock, a normal heart rate abnormal signal of the corresponding livestock is generated, and then the strength of the abnormal heart rate signal of the corresponding livestock is calculated. A thermal imaging camera is used to detect changes in temperature around the nostrils or mouth during breathing, and the number of breathing changes in one cycle is recorded, and the number of breathing changes in one cycle is used as the corresponding livestock breathing frequency; the corresponding livestock normal breathing frequency range is obtained from the database. If the livestock heart rate does not belong to the livestock normal breathing frequency range, the corresponding livestock normal breathing frequency abnormal signal is generated. Similarly, the corresponding livestock breathing frequency abnormal signal intensity is obtained.

7. A livestock inspection system according to claim 6, characterized in that: The specific process of comparing the physiological value SLZ with the preset intensity threshold to obtain the intensity coefficient is: If the physiological value SLZ is greater than the preset intensity threshold, the corresponding livestock body temperature abnormal signal intensity, the corresponding livestock normal heart rate abnormal signal intensity and the corresponding livestock normal respiratory rate abnormal signal intensity are multiplied by the corresponding preset signal strength weight factors to obtain the intensity coefficients, and the sizes are compared. If the corresponding intensity coefficient of the livestock body temperature abnormal signal intensity is the maximum value, the corresponding livestock body temperature abnormal signal is generated, and so on, the corresponding livestock heart rate abnormal signal and the corresponding livestock respiratory rate abnormal signal are generated.

8. A livestock inspection method, characterized in that: Applied to implement a livestock inspection system as described in any one of claims 1 to 7, the method comprises: S1: Obtain inspection data from different breeding areas QUN through livestock inspection equipment; S2: Analyze the inspection data and meteorological data of the breeding area QUN to obtain the available space volume and inspection frequency; S3: Perform abnormal analysis on the inspection data of QUN in different breeding areas through livestock inspection equipment to generate livestock abnormal temperature signals, heart rate abnormal signals, respiratory frequency abnormal signals and corresponding abnormal signal strengths and generate corresponding behavioral abnormal signals; S4: Take appropriate actions based on the signal generated in S3.

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