Intelligent dynamic monitoring method and system for livestock and poultry diseases
By clustering and modeling historical behavioral data of livestock and poultry, and combining reinforcement learning analysis, a health risk assessment matrix is generated, which solves the problem of low efficiency in livestock and poultry disease monitoring in existing technologies and realizes accurate assessment and early identification of livestock and poultry health status.
Patent Information
- Application Number
- CN202511135937.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-14
- Publication Date
- 2025-12-16
AI Technical Summary
Existing technologies for livestock and poultry disease monitoring lack a systematic approach to combining multi-source data for behavioral pattern analysis and risk assessment, resulting in low monitoring efficiency, slow response, and difficulty in achieving early identification and response to livestock and poultry diseases.
By acquiring historical behavioral data of livestock and poultry, clustering and numbering are performed to construct models of feeding range occupancy and activity range. These models are then analyzed using reinforcement learning to generate a health risk assessment matrix and implement response strategies to improve disease identification and response capabilities.
It enables precise assessment of livestock and poultry health status, improves the ability to identify and respond to diseases in their early stages, and enhances the intelligence and efficiency of livestock and poultry management.
Smart Images
Figure CN121148735A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of livestock disease intelligent dynamic monitoring, in particular to a livestock disease intelligent dynamic monitoring method and system. BACKGROUND
[0002] With the continuous development of animal husbandry, livestock health and safety has become a key factor for the sustainable development of the industry. Traditional livestock disease monitoring relies on manual inspection and experience-based judgment, which has the disadvantages of low monitoring efficiency, slow response and easy omission of early warning. In order to improve the detection efficiency and early warning ability of livestock diseases, intelligent monitoring technology has been gradually applied to animal husbandry in recent years. For example, a behavior monitoring system based on sensors can collect livestock activity and feeding data in real time, and combine big data analysis and machine learning algorithms to realize dynamic assessment of the health status of livestock groups.
[0003] However, most of the existing technologies focus on the monitoring of a single indicator, and lack of systematic analysis of behavior patterns and risk assessment based on multi-source data. Therefore, there is an urgent need for an intelligent monitoring method that integrates data collection, behavior analysis based on reinforcement learning, and risk assessment to improve the early identification and response capabilities of livestock diseases. SUMMARY
[0004] In view of the above-mentioned problems, in combination with the first aspect of the present application, the embodiments of the present application provide a livestock disease intelligent dynamic monitoring method, which comprises: acquiring historical behavior data of livestock, the historical behavior data comprising historical feeding range data and historical activity range data of livestock, clustering the livestock based on the historical feeding range data, acquiring dominant livestock groups and weak livestock groups, and numbering the dominant livestock groups and the weak livestock groups; analyzing the historical feeding range data based on reinforcement learning and constructing a feeding range occupation model, and analyzing the historical activity range data based on reinforcement learning and constructing an activity range model; acquiring real-time feeding range data and corresponding feeding time data of livestock, performing range occupation judgment on the real-time feeding range data and the corresponding feeding time data of livestock based on the feeding range occupation model, acquiring weak livestock numbers and dominant livestock numbers that are occupied, and generating an occupation event report; acquiring real-time activity range data of livestock, comparing the real-time activity range data with the historical activity range data, performing abnormality judgment on the comparison operation result based on the activity range model, acquiring abnormal activity range and corresponding livestock numbers, and generating an activity range mutation report; generating a health risk assessment matrix based on the occupation event report and the activity range mutation report; The risk level library is constructed, the health risk assessment matrix is input into the risk level library, the risk level of the livestock and poultry health state is divided based on the risk level library, and the corresponding response strategy is implemented.
[0005] As a further scheme of the present application, the historical behavior data includes historical feeding range data and historical activity range data of the livestock and poultry, the livestock and poultry are clustered based on the historical feeding range data, the dominant livestock and poultry group and the weak livestock and poultry group are obtained, and the dominant livestock and poultry group and the weak livestock and poultry group are numbered, comprising: The historical feeding range data and the historical activity range data of each livestock and poultry are obtained, and a feeding range threshold is set. If the historical feeding range data of the livestock and poultry is greater than or equal to the feeding range threshold, the livestock and poultry is clustered into the dominant livestock and poultry group. If the historical feeding range data of the livestock and poultry is less than the feeding range threshold, the livestock and poultry is clustered into the weak livestock and poultry group. At the same time, the dominant livestock and poultry group and the weak livestock and poultry group are numbered, and the dominant livestock and poultry number and the weak livestock and poultry number are obtained.
[0006] As a further scheme of the present application, the dominant livestock and poultry number and the weak livestock and poultry number are obtained, comprising: The dominant livestock and poultry number is represented as AX. Wherein, A represents the dominant livestock and poultry group, and X represents an ascending number starting from 1. The weak livestock and poultry number is represented as BY. Wherein, B represents the weak livestock and poultry group, and Y represents an ascending number starting from 1.
[0007] As a further scheme of the present application, the real-time feeding range data and the corresponding feeding time data of the livestock and poultry are obtained, the real-time feeding range data and the corresponding feeding time data of the livestock and poultry are judged based on the feeding range occupation model, the weak livestock and poultry number and the dominant livestock and poultry number are obtained, and the occupation event report is generated, comprising: The real-time feeding range data and the feeding time in the range of each livestock and poultry are obtained based on the obtaining module. Whether the real-time feeding range data exceeds the historical feeding range data is judged based on the historical behavior data. If the historical feeding range data is exceeded, the exceeding feeding range and the corresponding feeding time data are obtained. The exceeding feeding range and the corresponding feeding time data are judged based on the feeding range occupation model. If the occupation is successful, the weak livestock and poultry number and the feeding range after occupation are obtained. At the same time, the dominant livestock and poultry number and the feeding range after occupation are obtained. The occupation event report is generated based on the weak livestock and poultry number, the feeding range after occupation, the dominant livestock and poultry number, and the feeding range after occupation.
[0008] As a further scheme of the present application, the range occupation judgment comprises: If a certain livestock eats in the feeding range of another livestock for more than 30 seconds and is not driven away, it is indicated as a successful occupation. If a certain livestock eats in the feeding range of another livestock for more than 30 seconds and is not driven away, it is indicated as a successful occupation.
[0009] As a further scheme of the present application, the real-time activity range data of the livestock is acquired, the real-time activity range data is compared with historical activity range data, the comparison result is judged for abnormality based on the activity range model, the abnormal activity range and the corresponding livestock number are acquired, and an activity range mutation report is generated, comprising: The real-time activity range data of each livestock is acquired based on the acquisition module, and the real-time activity range data is compared with historical activity range data, an expanded activity range is acquired, and the expanded activity range is judged for abnormality based on the activity range model; If the expanded activity range exceeds a preset threshold, it is indicated that there is an abnormality, the abnormal activity range and the corresponding livestock number are acquired, and an activity range mutation report is generated based on the abnormal activity range and the corresponding livestock number.
[0010] As a further scheme of the present application, the health risk assessment matrix is generated based on the occupation event report and the activity range mutation report, comprising: The nutritional risk index is acquired based on the occupation event report, the infectious risk index is acquired based on the activity range mutation report, and the health risk assessment matrix is generated based on the nutritional risk index and the infectious risk index.
[0011] As a further scheme of the present application, the risk level library is constructed, the health risk assessment matrix is input into the risk level library, the risk level of the livestock is divided based on the risk level library, and the corresponding response strategy is implemented, comprising: The nutritional risk threshold and the infectious risk threshold are set, and four risk levels of a first risk, a second risk, a third risk and a fourth risk are set; The first risk indicates the health risk assessment matrix greater than or equal to the nutritional risk threshold and greater than or equal to the infectious risk threshold; The second risk indicates the health risk assessment matrix greater than or equal to the nutritional risk threshold and less than the infectious risk threshold; The third risk indicates the health risk assessment matrix less than the nutritional risk threshold and greater than or equal to the infectious risk threshold; The fourth risk indicates the health risk assessment matrix less than the nutritional risk threshold and less than the infectious risk threshold; The health risk assessment matrix is compared with the risk level library, and the corresponding response strategy is implemented based on the comparison operation.
[0012] As a further scheme of the present application, the operation of comparing the health risk assessment matrix with the risk level library comprises: If the livestock is obtained in the first risk level, it is indicated that the livestock suffers from infectious diseases and nutritional diseases, and the livestock is isolated, subjected to a physical examination and supplemented with nutrition; If the livestock is obtained in the second risk level, it is indicated that the livestock suffers from infectious diseases, and the livestock is isolated and subjected to a physical examination; If the livestock is obtained in the third risk level, it is indicated that the livestock suffers from nutritional diseases, and the livestock is supplemented with nutrition; If the livestock is obtained in the fourth risk level, it is indicated that the livestock neither suffers from infectious diseases nor nutritional diseases, and there is a possibility of a latent period, and the livestock is subjected to intensive monitoring.
[0013] In another aspect, the present application further provides a livestock disease intelligent dynamic monitoring system, comprising: An acquisition module, configured to acquire historical behavior data of livestock, wherein the historical behavior data comprises historical feeding range data and historical activity range data of the livestock, acquire real-time feeding range data and corresponding feeding time data of the livestock, and acquire real-time activity range data of the livestock; A clustering module, configured to cluster the livestock based on the historical feeding range data, acquire dominant livestock groups and weak livestock groups, and number the dominant livestock groups and the weak livestock groups; A construction module, configured to analyze the historical feeding range data based on reinforcement learning, and construct a feeding range occupation model, analyze the historical activity range data based on reinforcement learning, and construct an activity range model, and construct a risk level library; A judgment module, configured to perform range occupation judgment on the real-time feeding range data and the corresponding feeding time data of the livestock based on the feeding range occupation model, perform comparison operation on the real-time activity range data and the historical activity range data, and perform abnormality judgment on a comparison operation result based on the activity range model; A generation module, configured to generate an occupation event report, generate an activity range mutation report, and generate a health risk assessment matrix based on the occupation event report and the activity range mutation report; A response module, configured to input the health risk assessment matrix into the risk level library, divide the livestock into risk levels based on the risk level library, and implement a corresponding response strategy.
[0014] Based on the above aspects, the embodiment of the present application realizes obtaining historical behavior data of livestock and poultry, clustering livestock and poultry according to historical feeding range data, obtaining dominant livestock and poultry groups and weak livestock and poultry groups, and numbering the dominant livestock and poultry groups and the weak livestock and poultry groups, respectively analyzing the historical feeding range data and the activity range data through reinforcement learning, constructing a feeding range occupation model and an activity range model, and judging occupation events and abnormal activities in real time to provide accurate basis for health risk assessment and improve the intelligence and efficiency of livestock and poultry management, then obtaining real-time feeding range data and corresponding feeding time data of livestock and poultry, judging the real-time feeding range data and the corresponding feeding time data of livestock and poultry through the feeding range occupation model, obtaining the occupation weak livestock and poultry number and the occupied dominant livestock and poultry number, generating an occupation event report, obtaining real-time activity range data of livestock and poultry, comparing the real-time activity range data with historical activity range data, judging the comparison operation result according to the activity range model, obtaining abnormal activity range and corresponding livestock and poultry number, generating an activity range mutation report, generating a health risk assessment matrix through the occupation event report and the activity range mutation report, obtaining nutritional risk indicators and infectious risk indicators through multi-source data collection and behavior analysis of the feeding range and the activity range of livestock and poultry, and constructing a health risk assessment matrix for assessment, so as to determine whether livestock and poultry have nutritional diseases and infectious diseases, and through the intelligent detection method of multi-source data collection, behavior analysis and assessment, the diseases of livestock and poultry are detected.
[0015] Secondly, a risk level library is constructed, the health risk assessment matrix is input into the risk level library, the risk level library is used to divide the risk level of the health state of livestock and poultry, and the corresponding response strategy is implemented, and the multi-level response improves the early identification ability and disease coping ability of livestock and poultry. BRIEF DESCRIPTION OF DRAWINGS
[0016] Figure 1 is an execution flow schematic diagram of a livestock and poultry disease intelligent dynamic monitoring method provided by an embodiment of the present application.
[0017] Figure 2 is a schematic diagram of abnormal activity range of livestock and poultry in a livestock and poultry disease intelligent dynamic monitoring method provided by an embodiment of the present application.
[0018] Figure 3 is a schematic diagram of a livestock and poultry disease intelligent dynamic monitoring system provided by an embodiment of the present application. DETAILED DESCRIPTION
[0019] The present application will be specifically described below in combination with the drawings of the specification, Figure 1 is an execution flow schematic diagram of a livestock and poultry disease intelligent dynamic monitoring method provided by an embodiment of the present application, and the livestock and poultry disease intelligent dynamic monitoring method will be described in detail below.
[0020] Step S1: Obtain historical behavior data of livestock and poultry, including historical feeding range data and historical activity range data of livestock and poultry. Based on the historical feeding range data, cluster the livestock and poultry to obtain dominant and weak livestock and poultry groups, and assign numbers to the dominant and weak livestock and poultry groups.
[0021] In this embodiment, step S1 includes: Step S11: Obtain historical feeding range data and historical activity range data for each livestock and poultry, and set a feeding range threshold. If the historical feeding range data of livestock and poultry is greater than or equal to the feeding range threshold, they are clustered into a dominant livestock and poultry group. If the historical feeding range data of livestock and poultry is less than the feeding range threshold, they are clustered into a weak livestock and poultry group. At the same time, the dominant and weak livestock and poultry groups are numbered, and the dominant livestock and poultry number and the weak livestock and poultry number are obtained.
[0022] Specifically, a feeding range threshold is set based on historical feeding range data. The historical feeding range data of each chicken is compared with the feeding range threshold. Chickens with a feeding range greater than or equal to the feeding range threshold are clustered as dominant livestock and poultry groups, while chickens with a feeding range less than the feeding range threshold are clustered as vulnerable livestock and poultry groups.
[0023] For example, chicken farms feed chickens by placing food in chicken troughs. Based on historical feeding range data of 5-10 cm, a feeding range threshold of 8 cm is set. Chickens with historical feeding range data of 8-10 cm are classified as dominant livestock and poultry groups, while chickens with historical feeding range data of 5-8 cm are classified as weak livestock and poultry groups. The aforementioned historical feeding range refers to the area within the chicken trough.
[0024] It should be noted that chickens are territorial animals that compete for feeding and activity areas. They can also identify individuals in the group carrying infectious diseases. In this embodiment, the competition for feeding areas is judged by dividing the group into dominant and weak groups, thereby distinguishing nutritional diseases. In addition, the abnormality of activity areas is judged to distinguish infectious diseases. Using chickens as an example is representative.
[0025] Step S12, the dominant livestock and poultry number is represented as AX, where A represents the dominant livestock and poultry group and X represents an ascending number starting from 1.
[0026] The vulnerable livestock and poultry are denoted as BY, where B represents a vulnerable livestock and poultry group and Y represents an ascending number starting from 1.
[0027] For example, there are 100 chickens in a certain chicken coop, 48 of which are obtained as dominant chickens through clustering, and 52 of which are obtained as weak chickens. Each of the 48 dominant chickens is numbered from A1 to A48, and each of the 52 weak chickens is numbered from B1 to B52.
[0028] In step S2, the historical feeding range data is analyzed based on reinforcement learning, and a feeding range occupation model is constructed. The historical activity range data is analyzed based on reinforcement learning, and an activity range model is constructed.
[0029] It should be noted that the historical feeding range data and the historical activity range data of livestock and poultry can be analyzed using reinforcement learning methods such as Markov decision process, and feeding range occupation models and activity range models can be constructed respectively. The Markov decision process includes core elements such as state, action, reward, and state transition probability, and learns the optimal strategy through the interaction of the agent and the environment.
[0030] Specifically, for the feeding range occupation model, the environment is set as a feeding area containing resource distribution, the agent is a single or group of livestock and poultry, the state includes key information affecting occupation such as livestock and poultry position, surrounding livestock and poultry distribution and time, the action includes behaviors related to occupation such as moving out of the historical area, staying in the current historical area, being pushed into a smaller area, and the reward is designed according to the feedback of the weak group occupying the outside of the historical area in the historical data. After training, the model can judge the occupation relationship based on real-time state; for the activity range model, the environment is the overall activity area of livestock and poultry, the agent is a single livestock and poultry, the state includes current position, time, environmental factors, other livestock and poultry activity state and historical activity boundary, the action refers to moving direction, staying, moving distance and other activity behaviors, and the reward is set to positive or negative feedback according to whether it conforms to the historical regular activity range. After training, it can identify whether the real-time activity is abnormal. Both models learn behavior strategies through historical data training to provide a basis for subsequent judgment.
[0031] In step S3, real-time feeding range data and corresponding feeding time data of livestock and poultry are obtained, and the feeding range occupation model is used to judge the real-time feeding range data and corresponding feeding time data of livestock and poultry, to obtain the number of weak livestock and poultry and the number of strong livestock and poultry, and to generate an occupation event report.
[0032] In this embodiment, step S3 includes: In step S31, the real-time feeding range data of each livestock and poultry and the feeding time in the range are obtained based on the acquisition module, and the real-time feeding range data is judged based on the historical behavior data whether it exceeds the historical feeding range data. If it exceeds the historical feeding range data, the exceeded feeding range and corresponding feeding time data are obtained.
[0033] For example, the implementation of the number of B12 weak chicken eating range 9 cm, through the historical eating range 7 cm, get the eating range 2 cm, and in the eating time, while the eating range can be obtained by the dominant chicken A8 eating range.
[0034] Step S32, based on the eating range preemption model to exceed the eating range and corresponding eating time data range preemption judgment: If a certain livestock in the other livestock eating time in the eating range does not exceed thirty seconds and is driven, it is represented as preemption failure.
[0035] For example, the weak chicken B12 in the eating range of the dominant chicken A8 eats twenty seconds, and the weak chicken B12 is driven by the dominant chicken A8, which belongs to normal behavior, indicating that the eating range is preoccupied.
[0036] If a certain livestock in the other livestock eating time in the eating range exceeds thirty seconds and is not driven, it is represented as preemption success.
[0037] For example, the weak chicken B12 in the eating range of the dominant chicken A8 eats one minute, and the weak chicken B12 is not driven by the dominant chicken A8, which indicates that the eating range is preoccupied.
[0038] If the preemption is successful, the preoccupied weak livestock number and the preoccupied eating range are obtained, and the preoccupied dominant livestock number and the preoccupied eating range are obtained, and the preoccupied event report is generated based on the preoccupied weak livestock number, the preoccupied eating range, the preoccupied dominant livestock number and the preoccupied eating range.
[0039] Specifically, through the above judgment, if the weak chicken preoccupation is successful, the number of the preoccupied dominant chicken and the preoccupied eating range are obtained, and the number of the preoccupied weak chicken and the preoccupied eating range are obtained, and the number of the preoccupied dominant chicken and the preoccupied eating range, the number of the preoccupied weak chicken and the preoccupied eating range are generated preoccupied event report.
[0040] For example, the weak chicken B12 preoccupies the eating range of the dominant chicken A8 successfully, the historical eating range data of the weak chicken B12 is 7 cm, the historical eating range of the dominant chicken A8 is 9 cm, the eating range of the weak chicken B12 after preoccupation is 9 cm, and the eating range of the dominant chicken A8 is 7 cm, and the preoccupied event report is generated: the weak chicken B12 preoccupies the dominant chicken A8, the weak chicken B12 eating range is 9 cm, and the dominant chicken A8 eating range is 7 cm.
[0041] Further, the weak chicken preoccupied successfully is marked, and if the marked weak chicken exceeds three times preoccupation, the weak chicken is divided into the range of the dominant chicken.
[0042] It should be noted that the fighting for the feeding range is the nature of livestock and poultry, and the chicken is particularly obvious. If other chickens try to seize food, the chicken may exhibit aggressive behavior such as pecking or driving away the competitor. In general, the occurrence of the occupation of the feeding range is also the occupation of the feeding range of the weak chicken by the dominant chicken. If the weak chicken successfully occupies the feeding range of the dominant chicken, it proves that the dominant chicken has a disease. In the embodiment, whether the weak chicken successfully occupies the feeding range of the dominant chicken is judged to reflect whether the dominant chicken has a nutritional disease.
[0043] In step S4, the real-time activity range data of the livestock and poultry is acquired, the real-time activity range data is compared with the historical activity range data, the comparison operation result is judged to be abnormal based on the activity range model, the abnormal activity range and the corresponding livestock and poultry number are acquired, and the activity range mutation report is generated.
[0044] In the embodiment, step S4 includes: In step S41, the real-time activity range data of each livestock and poultry is acquired based on the acquisition module, the real-time activity range data is compared with the historical activity range data, the expanded activity range is acquired, and the expanded activity range is judged to be abnormal based on the activity range model.
[0045] Specifically, the historical activity range and the real-time activity range of each chicken are acquired, the real-time activity range data is compared with the historical activity range data, if it is found that the real-time activity range is greater than the historical activity range, the expanded activity range is acquired, and the expanded activity range is judged to be abnormal through the activity range model.
[0046] In step S41, if the expanded activity range exceeds the preset threshold value, it is indicated that there is an abnormality, the abnormal activity range and the corresponding livestock and poultry number are acquired, and the activity range mutation report is generated based on the abnormal activity range and the corresponding livestock and poultry number.
[0047] Specifically, the threshold value is set according to the activity range model, if the expanded activity range is greater than the threshold value, it is indicated that the expanded activity range is abnormal, the abnormal activity range and the corresponding livestock and poultry number are acquired, and the activity range mutation report is generated.
[0048] For example, the historical activity range of the chicken marked as A4 is 1 square meter, the real-time activity range of A4 is 4 square meters, the threshold value is set to 2 square meters according to the activity range model, it is indicated that the activity range of A4 is abnormal, the abnormal activity range is acquired by subtracting the set threshold value from the real-time activity range of A4, the activity range mutation report is generated: A4 activity anomaly, the abnormal activity range is 2 square meters; A17 activity anomaly, the abnormal activity range is 2.1 square meters; A24 activity anomaly, the abnormal activity range is 1.9 square meters.
[0049] It should be noted that when a group of chickens has a chicken with a disease, other chickens without the disease can distinguish whether they have the disease by observation and perception, such as abnormality in body posture, appearance change, smell or behavior, once they perceive that their companion has the disease, the healthy chickens will actively keep a distance, and the behavior of the chickens is an instinctive immune strategy to prevent the spread of the disease in the group.
[0050] Step S5, generating a health risk assessment matrix based on the pre-emption event report and the activity range mutation report.
[0051] Based on the pre-emption event report, a nutritional risk index is obtained, based on the activity range mutation report, an infectious risk index is obtained, and based on the nutritional risk index and the infectious risk index, a health risk assessment matrix is generated.
[0052] Specifically, the pre-emption range in the pre-emption event report is obtained, the pre-emption range is proportional to the nutritional risk index, and the nutritional risk index is represented as: Among them, is represented as a nutritional index, is represented as a pre-emption range.
[0053] For example, the pre-emption range is 2 cm, and the nutritional risk index is calculated to be 0.2.
[0054] Further, the abnormal activity base is obtained, and the base of the chicken is obtained, the abnormal activity proportion is obtained according to the base of the chicken and the abnormal activity base, the abnormal distance is obtained through the abnormal activity range, and the infectious risk index is represented as: Among them, is represented as an infectious risk index, is represented as an abnormal activity proportion, is represented as the minimum safe distance between individuals, that is, the sum of individual radii, is represented as an abnormal distance, is represented as a repulsion range.
[0055] It should be noted that the repulsion range of the chicken is usually 2.0.
[0056] For example, there are 100 chickens in a certain chicken coop, and the activity range of 3 chickens is abnormal, the sum of the individual radii of the two chickens is 0.3 meters, the abnormal distance is 3.3 meters, and the infectious index is calculated to be 0.036.
[0057] Step S6, constructing a risk level library, inputting the health risk assessment matrix into the risk level library, dividing the risk level of the livestock and poultry health state based on the risk level library, and implementing the corresponding response strategy.
[0058] In this embodiment, step S6 comprises: Step S61, set the nutritional risk threshold and infectious risk threshold, while setting the first risk, the second risk, the third risk and the fourth risk four risk levels.
[0059] Specifically, the nutritional risk threshold is set to 0.2, and the infectious risk threshold is set to 0.03.
[0060] The first risk is represented as a health risk assessment matrix greater than or equal to the nutritional risk threshold and greater than or equal to the infectious risk threshold.
[0061] For example, the obtained health risk assessment matrix is (0.26, 0.05), wherein the nutritional risk index is greater than the nutritional risk threshold and the infectious risk index is greater than the infectious risk threshold, indicating that the chicken corresponding to the health risk assessment matrix has the first risk.
[0062] The second risk is represented as a health risk assessment matrix greater than or equal to the nutritional risk threshold and less than the infectious risk threshold.
[0063] For example, the obtained health risk assessment matrix is (0.26, 0.02), wherein the nutritional risk index is greater than the nutritional risk threshold and the infectious risk index is less than the infectious risk threshold, indicating that the chicken corresponding to the health risk assessment matrix has the second risk.
[0064] The third risk is represented as a health risk assessment matrix less than the nutritional risk threshold and greater than or equal to the infectious risk threshold.
[0065] For example, the obtained health risk assessment matrix is (0.14, 0.05), wherein the nutritional risk index is less than the nutritional risk threshold and the infectious risk index is greater than the infectious risk threshold, indicating that the chicken corresponding to the health risk assessment matrix has the third risk.
[0066] The fourth risk is represented as a health risk assessment matrix less than the nutritional risk threshold and less than the infectious risk threshold.
[0067] For example, the obtained health risk assessment matrix is (0.14, 0.02), wherein the nutritional risk index is less than the nutritional risk threshold and the infectious risk index is less than the infectious risk threshold, indicating that the chicken corresponding to the health risk assessment matrix has the fourth risk.
[0068] The health risk assessment matrix is compared with the risk level library, and the corresponding response strategy is implemented based on the comparison operation.
[0069] Further, different response strategies are implemented for different risk levels.
[0070] Step S62, if the livestock and poultry is in the first risk level, it means that the livestock and poultry has infectious diseases and nutritional diseases, and the livestock and poultry is isolated, examined and supplemented with nutrition.
[0071] Specifically, if the corresponding chicken is in the first risk level, it means that the corresponding chicken has both infectious diseases and nutritional diseases, and the corresponding chicken is taken out of the chicken coop and isolated, examined and supplemented with nutrition.
[0072] If the livestock and poultry is in the second risk level, it means that the livestock and poultry has infectious diseases, and the livestock and poultry is isolated and examined.
[0073] Specifically, if the corresponding chicken is in the second risk level, it means that the corresponding chicken has only infectious diseases, and the corresponding chicken is taken out of the chicken coop and isolated and examined.
[0074] If the livestock and poultry is in the third risk level, it means that the livestock and poultry has nutritional diseases, and the livestock and poultry is supplemented with nutrition.
[0075] Specifically, if the corresponding chicken is in the third risk level, it means that the corresponding chicken has only nutritional diseases, and the corresponding chicken is supplemented with nutrition.
[0076] If the livestock and poultry is in the fourth risk level, it means that the livestock and poultry has neither infectious diseases nor nutritional diseases, and may be in the incubation period, and the livestock and poultry is monitored.
[0077] Specifically, if the corresponding chicken is in the first risk level, it means that the corresponding chicken has neither infectious diseases nor nutritional diseases, but may be in the incubation period, and the corresponding chicken is monitored.
[0078] Figure 2 A schematic diagram of the abnormal activity range of livestock and poultry in an intelligent dynamic livestock and poultry disease monitoring method provided by some embodiments of the present application is shown.
[0079] Specifically, the rectangular box represents the partial activity range of all livestock and poultry, the black triangle represents the livestock and poultry in the abnormal activity range, the dotted circle represents the historical activity range, the solid line represents the abnormal activity range, the white small circle and the black small circle both represent normal livestock and poultry, if there is no livestock and poultry in the abnormal activity range, it means that both the white small circle and the black small circle of normal livestock and poultry exist, if there is livestock and poultry in the abnormal activity range, it means that the normal livestock and poultry represented by the white small circle exits the solid line range, and only the normal livestock and poultry represented by the black small circle exists.
[0080] Figure 3 A schematic diagram of an intelligent dynamic livestock and poultry disease monitoring system provided by some embodiments of the present application is shown.
[0081] Specifically, an intelligent dynamic monitoring system for livestock and poultry diseases comprises: An acquisition module is configured to acquire historical behavior data of livestock and poultry, including historical feeding range data and historical activity range data of livestock and poultry, real-time feeding range data and corresponding feeding time data of livestock and poultry, and real-time activity range data of livestock and poultry.
[0082] A clustering module is configured to cluster livestock and poultry based on the historical feeding range data, acquire dominant livestock groups and weak livestock groups, and number the dominant livestock groups and the weak livestock groups.
[0083] A construction module is configured to analyze the historical feeding range data based on reinforcement learning, construct a feeding range occupation model, analyze the historical activity range data based on reinforcement learning, construct an activity range model, and construct a risk level library.
[0084] A judgment module is configured to make range occupation judgments on the real-time feeding range data and the corresponding feeding time data of livestock and poultry based on the feeding range occupation model, compare the real-time activity range data with the historical activity range data, and make abnormality judgments on the comparison results based on the activity range model.
[0085] A generation module is configured to generate an occupation event report, generate an activity range mutation report, and generate a health risk assessment matrix based on the occupation event report and the activity range mutation report.
[0086] A response module is configured to input the health risk assessment matrix into the risk level library, divide the risk levels of livestock and poultry based on the risk level library, and implement corresponding response strategies.
[0087] The specific use and effects of the embodiment are described as follows: Firstly, historical behavior data of livestock and poultry is acquired, livestock and poultry are clustered according to the historical feeding range data, dominant livestock and poultry groups and weak livestock and poultry groups are acquired, and the dominant livestock and poultry groups and the weak livestock and poultry groups are numbered, then feeding range occupation models and activity range models are constructed according to reinforcement learning, occupation events and abnormal activities are judged in real time, accurate basis is provided for health risk assessment, and the intelligentization and efficiency of livestock and poultry management are improved, then real-time feeding range data and corresponding feeding time data of livestock and poultry are acquired, the real-time feeding range data and the corresponding feeding time data of livestock and poultry are judged in range occupation by the feeding range occupation model, weak livestock and poultry numbers and strong livestock and poultry numbers are acquired, an occupation event report is generated, then real-time activity range data of livestock and poultry is acquired, the real-time activity range data is compared with historical activity range data, comparison operation results are judged in abnormality according to the activity range model, abnormal activity ranges and corresponding livestock and poultry numbers are acquired, an activity range mutation report is generated, a health risk assessment matrix is generated through the occupation event report and the activity range mutation report, finally, a risk level library is constructed, the health risk assessment matrix is input into the risk level library, the health state of livestock and poultry is divided into a risk level through the risk level library, and a corresponding response strategy is implemented, through multi-source data acquisition of feeding range and activity range of livestock and poultry and behavior analysis, nutritional risk indicators and infectious risk indicators are acquired, and a health risk assessment matrix is constructed for assessment, so as to determine whether livestock and poultry have nutritional diseases and infectious diseases, through the intelligent detection method of multi-source data acquisition, behavior analysis and assessment, livestock and poultry are detected for diseases, and through multi-level response, early identification ability and disease response ability of livestock and poultry are improved.
[0088] In addition, the embodiment of the present application further provides an electronic device, comprising: At least one processor; and a memory connected with the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method proposed in the embodiment of the present application.
[0089] The various constituent components of the electronic device will be specifically introduced as follows: The processor is the control center of the electronic device, and can be one processor or a combination of multiple processing elements. For example, the processor is one or more central processing units (CPUs), application specific integrated circuits (ASICs), or one or more integrated circuits configured to implement an embodiment of the present application, such as one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs).
[0090] The processor can execute various functions of the electronic device by running or executing software programs stored in the memory and calling data stored in the memory.
[0091] The memory is used to store software programs for implementing the present application, and is controlled by the processor to execute. The specific implementation manner can refer to the above method embodiments, and will not be described here.
[0092] The memory can be a real-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only (CD-ROM), or other optical disk storage, optical disk storage (including compact disks, laser disks, optical disks, digital versatile disks, Blu-ray disks, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and capable of being accessed by a computer, but not limited to the above. The memory can be integrated with the processor or exist independently and coupled to the processor through the interface circuit of the electronic device, and the present application is not limited in this regard.
[0093] The above-described embodiments can be implemented in whole or in part by software, hardware (such as a circuit), firmware, or any combination thereof. When implemented in software, the above-described embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center by limited (for example, infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center, etc. containing one or more available medium collections. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid state disk.
[0094] It should be understood that the term "and / or" herein merely describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the existence of A alone, the existence of A and B, and the existence of B alone, where A and B can be singular or plural. In addition, the character " / " herein generally represents that the associated objects before and after are an "or" relationship, but can also represent an "and / or" relationship, which can be understood according to the context before and after.
[0095] It should be understood that in the embodiments of the present application, the size of the sequence number of the above-mentioned processes does not mean the order of execution, and the execution order of the processes should be determined according to their functions and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.
[0096] The above-described embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.
Claims
1. A livestock disease intelligent dynamic monitoring method, characterized in that, The method comprises: acquiring historical behavior data of livestock and poultry, the historical behavior data comprising historical feeding range data and historical activity range data of livestock and poultry, clustering livestock and poultry based on the historical feeding range data, acquiring dominant livestock and poultry groups and weak livestock and poultry groups, and numbering the dominant livestock and poultry groups and the weak livestock and poultry groups; analyzing the historical feeding range data based on reinforcement learning and constructing a feeding range occupation model, and analyzing the historical activity range data based on reinforcement learning and constructing an activity range model; acquiring real-time feeding range data and corresponding feeding time data of livestock and poultry, performing range occupation judgment on the real-time feeding range data and the corresponding feeding time data of livestock and poultry based on the feeding range occupation model, acquiring weak livestock and poultry numbers and dominant livestock and poultry numbers that are occupied, and generating an occupation event report; acquiring real-time activity range data of livestock and poultry, performing comparison operation on the real-time activity range data and the historical activity range data, performing abnormality judgment on the comparison operation result based on the activity range model, acquiring abnormal activity range and corresponding livestock and poultry numbers, and generating an activity range mutation report; generating a health risk assessment matrix based on the occupation event report and the activity range mutation report; constructing a risk level library, inputting the health risk assessment matrix into the risk level library, dividing the health status of livestock and poultry into risk levels based on the risk level library, and implementing corresponding response strategies.
2. The intelligent dynamic monitoring method for livestock and poultry diseases according to claim 1, characterized in that, The acquiring of the historical behavior data of livestock and poultry, the historical behavior data comprising historical feeding range data and historical activity range data of livestock and poultry, the clustering of livestock and poultry based on the historical feeding range data, the acquiring of dominant livestock and poultry groups and weak livestock and poultry groups, and the numbering of the dominant livestock and poultry groups and the weak livestock and poultry groups comprise: acquiring historical feeding range data and historical activity range data of each livestock and poultry, and setting a feeding range threshold value, if the historical feeding range data of livestock and poultry is greater than or equal to the feeding range threshold value, clustering as a dominant livestock and poultry group, if the historical feeding range data of livestock and poultry is less than the feeding range threshold value, clustering as a weak livestock and poultry group, and simultaneously numbering the dominant livestock and poultry groups and the weak livestock and poultry groups to acquire dominant livestock and poultry numbers and weak livestock and poultry numbers.
3. The intelligent dynamic monitoring method for livestock and poultry diseases according to claim 2, characterized in that, The acquiring of the dominant livestock and poultry numbers and the weak livestock and poultry numbers comprises: The dominant livestock and poultry number is represented as AX. Wherein, A represents a dominant livestock and poultry group, and X represents an ascending number starting from 1. The weak livestock and poultry number is represented as BY. Wherein, B represents a weak livestock and poultry group, and Y represents an ascending number starting from 1.
4. The intelligent dynamic monitoring method for livestock and poultry diseases according to claim 1, characterized in that, The acquiring of real-time feeding range data and corresponding feeding time data of livestock and poultry, the range occupation judgment on the real-time feeding range data and the corresponding feeding time data of livestock and poultry based on the feeding range occupation model, the acquiring of weak livestock and poultry numbers and dominant livestock and poultry numbers that are occupied, and the generation of an occupation event report comprise: acquiring real-time feeding range data and feeding time within the range of each livestock and poultry based on an acquisition module, judging whether the real-time feeding range data exceeds the historical feeding range data based on the historical behavior data, if the real-time feeding range data exceeds the historical feeding range data, acquiring the exceeded feeding range and corresponding feeding time data; The range preemption judgment is based on the eating range preemption model, and if preemption is successful, the preemption-weak livestock number and the preemption eating range are obtained, and the preemption-strong livestock number and the preemption eating range are obtained. The preemption event report is generated based on the preemption-weak livestock number, the preemption eating range, the preemption-strong livestock number, and the preemption eating range.
5. The intelligent dynamic monitoring method for livestock and poultry diseases according to claim 4, characterized in that, The range preemption judgment includes: If a certain livestock eats in the eating range of another livestock for no more than thirty seconds and is driven away, it means preemption failure; If a certain livestock eats in the eating range of another livestock for more than thirty seconds and is not driven away, it means preemption success.
6. The intelligent dynamic monitoring method for livestock and poultry diseases according to claim 1, characterized in that, The real-time activity range data of the livestock is obtained, and the real-time activity range data is compared with the historical activity range data. The comparison result is abnormally judged based on the activity range model, the abnormal activity range and the corresponding livestock number are obtained, and the activity range mutation report is generated, including: The real-time activity range data of each livestock is obtained based on the acquisition module, and the real-time activity range data is compared with the historical activity range data. The enlarged activity range is obtained, and the enlarged activity range is abnormally judged based on the activity range model. If the enlarged activity range exceeds the preset threshold, it means that there is an abnormality. The abnormal activity range and the corresponding livestock number are obtained, and the activity range mutation report is generated based on the abnormal activity range and the corresponding livestock number.
7. The intelligent dynamic monitoring method for livestock and poultry diseases according to claim 1, characterized in that, The health risk assessment matrix is generated based on the preemption event report and the activity range mutation report, including: The nutritional risk index is obtained based on the preemption event report, the infectious risk index is obtained based on the activity range mutation report, and the health risk assessment matrix is generated based on the nutritional risk index and the infectious risk index.
8. The intelligent dynamic monitoring method for livestock and poultry diseases according to claim 1, characterized in that, The risk level library is constructed, the health risk assessment matrix is input into the risk level library, the risk level of the livestock is divided based on the risk level library, and the corresponding response strategy is implemented, including: The nutritional risk threshold and the infectious risk threshold are set, and the first risk, the second risk, the third risk, and the fourth risk are set as four risk levels; The first risk means that the health risk assessment matrix is greater than or equal to the nutritional risk threshold and greater than or equal to the infectious risk threshold; The second risk means that the health risk assessment matrix is greater than or equal to the nutritional risk threshold and less than the infectious risk threshold; The third risk means that the health risk assessment matrix is less than the nutritional risk threshold and greater than or equal to the infectious risk threshold; The fourth risk means that the health risk assessment matrix is less than the nutritional risk threshold and less than the infectious risk threshold; The health risk assessment matrix is compared with the risk level library, and the corresponding response strategy is implemented based on the comparison operation.
9. The intelligent dynamic monitoring method for livestock and poultry diseases according to claim 8, characterized in that, The health risk assessment matrix is compared with the risk level library, and the corresponding response strategy is implemented based on the comparison operation, including: If the livestock is in the first risk level, it means that the livestock has infectious diseases and nutritional diseases. The livestock is isolated, examined, and supplemented with nutrients. If the livestock is in the second risk level, it is indicated that the livestock has infectious diseases, and the livestock is isolated and subjected to a full-body examination; If the livestock is in the third risk level, it is indicated that the livestock has nutritional diseases, and the livestock is subjected to nutritional supplementation; If the livestock is in the fourth risk level, it is indicated that the livestock neither has infectious diseases nor nutritional diseases, and there may be a latent period, and the livestock is subjected to intensive monitoring.
10. An intelligent dynamic monitoring system for livestock diseases, characterized in that, The method comprises the following steps: an acquisition module is configured to acquire historical behavior data of livestock, the historical behavior data comprising historical feeding range data and historical activity range data of the livestock, real-time feeding range data and corresponding feeding time data of the livestock, and real-time activity range data of the livestock; a clustering module is configured to cluster the livestock based on the historical feeding range data, acquire dominant livestock groups and weak livestock groups, and number the dominant livestock groups and the weak livestock groups; a construction module is configured to analyze the historical feeding range data based on reinforcement learning, construct a feeding range occupation model, analyze the historical activity range data based on reinforcement learning, construct an activity range model, and construct a risk level library; a judgment module is configured to perform range occupation judgment on the real-time feeding range data and the corresponding feeding time data of the livestock based on the feeding range occupation model, perform comparison operation on the real-time activity range data and the historical activity range data, and perform abnormality judgment on the comparison operation result based on the activity range model; a generation module is configured to generate an occupation event report, generate an activity range mutation report, and generate a health risk assessment matrix based on the occupation event report and the activity range mutation report; a response module is configured to input the health risk assessment matrix into the risk level library, divide the livestock into risk levels based on the risk level library, and implement a corresponding response strategy.