A data monitoring method and system for livestock and poultry activities

Abstract

The invention discloses a data monitoring method and system for livestock and poultry activities, and relates to the technical field of data monitoring. The electromagnetic interference coefficient and the temperature and humidity influence coefficient are respectively calculated by collecting the electromagnetic interference signal and the temperature and humidity of the environment in which the sensor is located when acquiring the livestock and poultry activity data; the data acquisition timestamp of the sensor when acquiring the livestock and poultry activity data is collected to calculate the acquisition time fluctuation coefficient; the data unqualified coefficient is calculated according to the electromagnetic interference coefficient, the temperature and humidity influence coefficient and the acquisition time fluctuation coefficient, and it is judged whether the health status and behavior pattern of the livestock and poultry can be monitored through the livestock and poultry activity data acquired by the sensor according to the data unqualified coefficient and a preset threshold value; in this way, it is possible to judge whether the livestock and poultry activity data acquired by the sensor are consistent with the actual livestock and poultry activity data, and respond in time to ensure that the analyzed health status and behavior pattern of the livestock and poultry are correct and in line with reality, so that farmers can make correct decision support.

Description

Technical Field

[0001] The present invention relates to the technical field of data monitoring, and in particular to a data monitoring method and system for livestock and poultry activities. Background Art

[0002] Data monitoring of livestock and poultry activities is a key link in smart farming. It aims to collect the activity trajectories, behavioral characteristics, and physiological parameters of livestock and poultry in real time through technical means such as sensors, cameras, and wearable devices. These data can be used to analyze the health status and behavioral patterns of livestock and poultry, thereby achieving refined management, early warning of diseases, and improved farming efficiency. At present, common monitoring technologies include video surveillance and sensors. These technologies upload the collected data to the cloud or local server, and use artificial intelligence or data mining technology to analyze it to provide decision support for farmers.

[0003] Among them, sensor technology plays a core role in data monitoring of livestock and poultry activities, and can accurately capture multi-dimensional data of individuals; through wearable sensors (such as GPS, accelerometers, and body temperature sensors), the activity trajectory, physiological state, and behavioral characteristics of livestock and poultry can be obtained in real time, realizing all-round monitoring from individuals to groups. The real-time and accuracy of sensors enable abnormal behaviors or health problems to be quickly located and fed back, providing key support for efficient breeding and precise management.

[0004] However, in the actual data monitoring of livestock and poultry activities, if an error occurs in the sensor, the acquired livestock and poultry activity data will be inconsistent with the actual livestock and poultry activity data. If it is still uploaded to the cloud or local server, it may cause errors in the health status and behavior patterns of the analyzed livestock and poultry, causing farmers to make wrong decision support. Summary of the invention

[0005] The purpose of the present invention is to solve the above-mentioned problems and provide a data monitoring method and system for livestock and poultry activities.

[0006] In a first aspect of the present invention, a data monitoring method for livestock and poultry activities is first proposed, the method comprising:

[0007] Collect electromagnetic interference signals of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculate the electromagnetic interference coefficient based on the electromagnetic interference signals;

[0008] Collect the temperature and humidity of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculate the temperature and humidity influence coefficient based on the temperature and humidity;

[0009] Collect the data acquisition timestamp when the sensor acquires livestock and poultry activity data, and calculate the acquisition time fluctuation coefficient based on the data acquisition timestamp;

[0010] The data unqualified coefficient is calculated based on the electromagnetic interference coefficient, the temperature and humidity influence coefficient, and the collection time fluctuation coefficient. Based on the data unqualified coefficient and the preset data unqualified coefficient threshold, it is determined whether the health status and behavior patterns of livestock and poultry can be monitored through the livestock and poultry activity data obtained by the sensor.

[0011] Optionally, calculating the electromagnetic interference coefficient according to the electromagnetic interference signal includes:

[0012] The time interval during which the sensor obtains livestock and poultry activity data is recorded as the target time interval, and the electromagnetic interference signal of the sensor in the target time interval is obtained and marked as ,in, , is a positive integer, Indicates the number of electromagnetic interference signals;

[0013] use Wavelet basis function for each electromagnetic interference signal obtained Perform continuous wavelet transform. , the electromagnetic interference signal is decomposed in the time domain and frequency domain, as follows: ; In the formula, are the wavelet coefficients, It is an electromagnetic interference signal. is the selected wavelet basis function, is the scale parameter, which is used to adjust the scale of the wavelet basis function; is the translation parameter, which is used to adjust the position of the wavelet basis function; Represents the time coordinate of the signal, that is, the position on the time axis;

[0014] Extract the energy characteristics of the wavelet coefficients. According to the calculated wavelet coefficients, further extract the energy characteristics and calculate the energy of the wavelet coefficients at each scale. The calculation formula is as follows: ; In the formula, is in scale The energy below is the wavelet coefficient, and then the energy of the wavelet coefficients at different scales is summed to obtain the comprehensive energy characteristics ;

[0015] Calculate the electromagnetic interference index of each electromagnetic interference signal, and the calculation expression is: , where is the electromagnetic interference index;

[0016] All electromagnetic interference index Add them together to get the electromagnetic interference coefficient, and the calculation formula is: , where is the electromagnetic interference coefficient.

[0017] Optionally, calculating the temperature and humidity influence coefficient according to the temperature and humidity includes:

[0018] The time interval when the sensor obtains livestock and poultry activity data is recorded as the target time interval, and the temperature and humidity of the environment where the sensor is located in the target time interval are obtained. The temperature and humidity influence coefficient is calculated according to the temperature and humidity of the environment. The calculation formula is:

[0019]

[0020] in, is the temperature and humidity influence coefficient, , Respectively represent the temperature and humidity of the environment, [ , ] indicates the time period when the ambient temperature is outside the preset effective operating temperature range of the sensor. [ , ] indicates the time period when the humidity of the environment is outside the preset effective working humidity range of the sensor; and are the preset proportional coefficients for temperature and humidity, respectively, and and Both are greater than 0.

[0021] Optionally, calculating the collection time fluctuation coefficient according to the data collection timestamp includes:

[0022] The time interval in which the sensor obtains livestock and poultry activity data is recorded as the target time interval, and the data acquisition timestamp in the target time interval is obtained to obtain a timestamp sequence based on time order;

[0023] Calculate the time interval between every two adjacent time stamps in the time stamp sequence as the response time interval, and obtain a response interval sequence based on the time order;

[0024] The response interval in the response interval sequence is calibrated as , Indicates the order number of the response interval in the response interval sequence, , is the total number of response intervals in the response interval sequence, and is a positive integer;

[0025] Calculate the mean of the response interval series. The calculation formula is: ,in, is the mean of the response interval series;

[0026] Calculate the acquisition time fluctuation coefficient, the calculation formula is: ,in, is the acquisition time fluctuation coefficient.

[0027] Optionally, the data unqualified coefficient is calculated according to the electromagnetic interference coefficient, the temperature and humidity influence coefficient and the collection time fluctuation coefficient, including:

[0028]

[0029] In the formula, is the data failure coefficient, , , They are electromagnetic interference coefficient, temperature and humidity influence coefficient, and collection time fluctuation coefficient. They are , , The preset scaling factor of Both are greater than 0.

[0030] Optionally, judging whether the health status and behavior pattern of livestock and poultry can be monitored through livestock and poultry activity data obtained by sensors according to the data unqualified coefficient and the preset data unqualified coefficient threshold includes:

[0031] If the data unqualified coefficient is less than the preset data unqualified coefficient threshold, the health status and behavior pattern of the livestock and poultry can be monitored through the livestock and poultry activity data obtained by the sensor;

[0032] If the data unqualified coefficient is not less than the preset data unqualified coefficient threshold, the health status and behavior patterns of livestock and poultry cannot be monitored through the livestock and poultry activity data obtained by the sensor; an alarm signal is issued at this time.

[0033] In a second aspect of the present invention, a data monitoring system for livestock and poultry activities is provided, the system comprising:

[0034] Electromagnetic interference module: collects electromagnetic interference signals from the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculates the electromagnetic interference coefficient based on the electromagnetic interference signals;

[0035] Temperature and humidity impact module: collects the temperature and humidity of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculates the temperature and humidity impact coefficient based on the temperature and humidity;

[0036] Collection time fluctuation module: collects the data collection timestamp when the sensor acquires livestock and poultry activity data, and calculates the collection time fluctuation coefficient based on the data collection timestamp;

[0037] Monitoring module: Calculate the data unqualified coefficient based on the electromagnetic interference coefficient, temperature and humidity influence coefficient and collection time fluctuation coefficient, and determine whether the health status and behavior patterns of livestock and poultry can be monitored through the livestock and poultry activity data obtained by the sensor based on the data unqualified coefficient and the preset data unqualified coefficient threshold.

[0038] Beneficial effects of the present invention:

[0039] The present invention proposes a data monitoring method and system for livestock and poultry activities, which calculates the electromagnetic interference coefficient by collecting electromagnetic interference signals of the environment in which the sensor is located when acquiring livestock and poultry activity data;

[0040] The temperature and humidity of the environment in which the sensor is located when acquiring livestock and poultry activity data are collected to calculate the temperature and humidity influence coefficient; the data acquisition timestamp when the sensor acquires livestock and poultry activity data is collected to calculate the acquisition time fluctuation coefficient; the data unqualified coefficient is calculated according to the electromagnetic interference coefficient, the temperature and humidity influence coefficient and the acquisition time fluctuation coefficient, and the data unqualified coefficient and the preset data unqualified coefficient threshold are used to determine whether the health status and behavior patterns of livestock and poultry can be monitored through the livestock and poultry activity data acquired by the sensor; in this way, in the actual data monitoring of livestock and poultry activities, it is possible to determine whether the livestock and poultry activity data acquired by the sensor is consistent with the actual livestock and poultry activity data, and respond in a timely manner to ensure that the analyzed health status and behavior patterns of livestock and poultry are correct and in line with reality, so that farmers can make correct decision support. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The present invention will be further described below in conjunction with the accompanying drawings.

[0042] Figure 1 A flowchart of a data monitoring method for livestock and poultry activities;

[0043] Figure 2 The figure is a framework diagram of a data monitoring system for livestock and poultry activities. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

[0046] The embodiment of the present invention provides a method for monitoring data of livestock and poultry activities. Figure 1 , Figure 1 A flow chart of a method for monitoring livestock and poultry activities provided by an embodiment of the present invention. The method comprises the following steps:

[0047] Collect electromagnetic interference signals of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculate the electromagnetic interference coefficient based on the electromagnetic interference signals;

[0048] Collect the temperature and humidity of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculate the temperature and humidity influence coefficient based on the temperature and humidity;

[0049] Collect the data acquisition timestamp when the sensor acquires livestock and poultry activity data, and calculate the acquisition time fluctuation coefficient based on the data acquisition timestamp;

[0050] The data unqualified coefficient is calculated based on the electromagnetic interference coefficient, the temperature and humidity influence coefficient, and the collection time fluctuation coefficient. Based on the data unqualified coefficient and the preset data unqualified coefficient threshold, it is determined whether the health status and behavior patterns of livestock and poultry can be monitored through the livestock and poultry activity data obtained by the sensor.

[0051] Based on a data monitoring method for livestock and poultry activities provided by an embodiment of the present invention, through the above-mentioned method, in the actual data monitoring of livestock and poultry activities, it is possible to judge whether the data of livestock and poultry activities obtained by the sensor is consistent with the actual data of livestock and poultry activities, and respond in a timely manner to ensure that the health status and behavior patterns of the analyzed livestock and poultry are correct and in line with reality, so as to support farmers in making correct decisions.

[0052] In one embodiment, collecting electromagnetic interference signals of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculating the electromagnetic interference coefficient according to the electromagnetic interference signals includes:

[0053] The time interval during which the sensor obtains livestock and poultry activity data is recorded as the target time interval, and the electromagnetic interference signal of the sensor in the target time interval is obtained and marked as ,in, , is a positive integer, Indicates the number of electromagnetic interference signals;

[0054] use Wavelet basis function for each electromagnetic interference signal obtained Perform continuous wavelet transform. , the electromagnetic interference signal is decomposed in the time domain and frequency domain, as follows: ; In the formula, are the wavelet coefficients, It is an electromagnetic interference signal. is the selected wavelet basis function, is the scale parameter, which is used to adjust the scale of the wavelet basis function; is the translation parameter, which is used to adjust the position of the wavelet basis function; Represents the time coordinate of the signal, that is, the position on the time axis;

[0055] Extract the energy characteristics of the wavelet coefficients. According to the calculated wavelet coefficients, further extract the energy characteristics and calculate the energy of the wavelet coefficients at each scale. The calculation formula is as follows: ; In the formula, is in scale The energy below is the wavelet coefficient, and then the energy of the wavelet coefficients at different scales is summed to obtain the comprehensive energy characteristics ;

[0056] Calculate the electromagnetic interference index of each electromagnetic interference signal, and the calculation expression is: , where is the electromagnetic interference index;

[0057] All electromagnetic interference index Add them together to get the electromagnetic interference coefficient, and the calculation formula is: , where is the electromagnetic interference coefficient.

[0058] It should be noted that the acquisition method of electromagnetic interference signals in the environment where the sensor is located when acquiring livestock and poultry activity data can be achieved through a specially designed electromagnetic interference monitoring module; this module senses electromagnetic waves in the surrounding environment, including radio frequency (RF) signals, wireless communication signals and other possible electromagnetic wave sources, and collects electromagnetic signal strength, frequency and waveform characteristics in real time; these signals are captured through the wireless receiving function of the sensor and recorded in the data storage module of the sensor. Then, these raw signals are transmitted to the processing unit for further analysis to extract the characteristic information of electromagnetic interference for wavelet transformation and energy analysis; it can also be his acquisition method, which is not limited or elaborated in detail.

[0059] It should be noted that the larger the electromagnetic interference coefficient, the greater the possibility of errors in the sensors that obtain livestock and poultry activity data, and the greater the possibility that the livestock and poultry activity data obtained by the sensor is inconsistent with the actual livestock and poultry activity data. If it is still uploaded to the cloud or local server, it may cause errors in the health status and behavior patterns of the analyzed livestock and poultry, causing farmers to make wrong decision support. The reason is that electromagnetic interference will directly affect the signal acquisition and transmission quality of the sensor; when the electromagnetic interference coefficient is large, the signal received by the sensor will be affected by external interference, resulting in signal distortion or loss, which in turn affects the accuracy and reliability of the data. For example, electromagnetic interference may cause the sensor to fail to accurately record the real behavior and physiological parameters of livestock and poultry when collecting livestock and poultry activity data, and may even completely mistakenly collect false data. If such data errors are uploaded to the cloud or local server for analysis without effective screening and processing, they will introduce deviations in subsequent health monitoring and behavior pattern analysis. Ultimately, farmers may make incorrect judgments based on these inaccurate data, affecting the correctness of breeding decisions, such as misjudging the health status of livestock and poultry, misjudging the occurrence of diseases, or incorrectly adjusting breeding management strategies, which may even lead to unnecessary waste of resources or increased health risks. Therefore, the greater the electromagnetic interference coefficient, the greater the risk of data inaccuracy, and effective means must be taken to detect and correct it to ensure the accuracy of livestock and poultry activity data and the reliability of decision support.

[0060] In one implementation method, the benefits of analyzing the electromagnetic interference coefficient for determining whether the livestock and poultry activity data obtained by sensors can monitor the health status and behavior patterns of livestock and poultry are: it can promptly detect whether the sensor is affected by external interference, thereby determining whether the data truly reflects the actual activities and health status of livestock and poultry; the analysis of the electromagnetic interference coefficient helps to automatically screen and correct data during data transmission, avoid erroneous data from being uploaded to the cloud or local server, and prevent the resulting misjudgment from having a negative impact on health monitoring, behavior analysis and breeding decisions; through effective control of electromagnetic interference, the intelligence level of the system can be improved, the accuracy of monitoring can be improved, more reliable decision-making support can be provided to farmers, and breeding management efficiency and animal health protection can be improved.

[0061] In one embodiment, collecting the temperature and humidity of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculating the temperature and humidity influence coefficient according to the temperature and humidity includes:

[0062] The time interval when the sensor obtains livestock and poultry activity data is recorded as the target time interval, and the temperature and humidity of the environment where the sensor is located in the target time interval are obtained. The temperature and humidity influence coefficient is calculated according to the temperature and humidity of the environment. The calculation formula is:

[0063]

[0064] in, is the temperature and humidity influence coefficient, , Respectively represent the temperature and humidity of the environment, [ , ] indicates the time period when the ambient temperature is outside the preset effective operating temperature range of the sensor. [ , ] indicates the time period when the humidity of the environment is outside the preset effective working humidity range of the sensor; and are the preset proportional coefficients for temperature and humidity, respectively, and and Both are greater than 0.

[0065] It should be noted that and It is set by professionals according to the actual situation. Generally, and The sum of is 1;

[0066] It should be noted that the temperature and humidity of the environment in which the sensor is located when acquiring livestock and poultry activity data can be monitored in real time through the built-in temperature and humidity sensor. Usually, these sensors can continuously measure the temperature and humidity in the environment and record the data in the form of a time series. The sensor directly senses the changes in temperature and humidity of the surrounding environment through the integrated temperature and humidity probe, and collects and stores the data in real time. In order to ensure the accuracy of the data, the sensor usually performs self-calibration regularly, and may be equipped with a transmission module to upload the temperature and humidity data to a local server or cloud platform for further processing. In the area where the sensor is located, changes in ambient temperature and humidity will be fed back in a timely manner through these devices to help determine the impact of external environmental factors on the quality of data acquisition; in addition, the sensor preset effective operating temperature range and the sensor preset effective operating temperature range are set by professionals based on actual conditions, and are not specifically limited or elaborated.

[0067] It should be noted that when the temperature and humidity influence coefficient is larger, the possibility of sensor error in obtaining livestock and poultry activity data is greater, and the possibility of inconsistency between the livestock and poultry activity data obtained by the sensor and the actual livestock and poultry activity data is also greater. If it is still uploaded to the cloud or local server, it may cause errors in the analyzed health status and behavior patterns of livestock and poultry, leading to farmers making wrong decision support. The reason is that the change of temperature and humidity has an important impact on the working stability and measurement accuracy of the sensor. When the temperature and humidity exceed the effective working range of the sensor, the performance of the sensor may be affected, resulting in errors in data collection; for example, too high or too low temperature may cause the internal circuit of the sensor to overheat or freeze, affecting the stability of the signal; and too high or too low humidity may cause the sensor's sensing element to become damp or dry, reducing its response speed and accuracy. When the temperature and humidity influence coefficient is large, it means that the sensor is working in an unsuitable environment, which causes the collected data to deviate from the actual livestock and poultry activity. If these inaccurate data are uploaded to the cloud or local server for health status and behavior pattern analysis without effective processing, it may lead to misjudgment of the health status of livestock and poultry, or even incorrectly identify disease symptoms or ignore potential health problems. The decision support made by farmers based on these erroneous data may miss the best time for intervention, affect breeding efficiency, and may even lead to unnecessary waste of resources or expansion of health risks. Therefore, monitoring and adjusting the temperature and humidity influence coefficients are crucial to ensure the accuracy of data and the scientific nature of decision-making.

[0068] In one implementation method, the benefit of analyzing the temperature and humidity influence coefficient for determining whether the livestock and poultry activity data obtained by the sensor can monitor the health status and behavior patterns of livestock and poultry is that it can effectively evaluate the potential interference of environmental factors on the quality of sensor data, thereby providing a guarantee for the accuracy of the data. By timely monitoring and adjusting the temperature and humidity influence coefficient, errors caused by abnormal environmental temperature and humidity can be avoided, ensuring that the data obtained by the sensor truly reflects the actual activities and physiological conditions of livestock and poultry. Secondly, the temperature and humidity influence coefficient can provide a reference for data screening and cleaning, thereby avoiding misleading health monitoring and behavior pattern analysis, helping farmers identify outliers in the data, and avoiding wrong judgments or decisions caused by inaccurate data. In addition, through quantitative analysis of the impact of temperature and humidity, farmers can more accurately grasp the changes in the living environment of livestock and poultry, adjust environmental conditions to improve the health management level of livestock and poultry, and further improve breeding efficiency and benefits.

[0069] In one embodiment, collecting the data acquisition timestamp when the sensor acquires the livestock and poultry activity data, and calculating the acquisition time fluctuation coefficient according to the data acquisition timestamp includes:

[0070] The time interval in which the sensor obtains livestock and poultry activity data is recorded as the target time interval, and the data acquisition timestamp in the target time interval is obtained to obtain a timestamp sequence based on time order;

[0071] Calculate the time interval between every two adjacent time stamps in the time stamp sequence as the response time interval, and obtain a response interval sequence based on the time order;

[0072] The response interval in the response interval sequence is calibrated as , Indicates the order number of the response interval in the response interval sequence, , is the total number of response intervals in the response interval sequence, and is a positive integer;

[0073] Calculate the mean of the response interval series. The calculation formula is: ,in, is the mean of the response interval series;

[0074] Calculate the acquisition time fluctuation coefficient, the calculation formula is: ,in, is the acquisition time fluctuation coefficient.

[0075] It should be noted that the data collection timestamp of the sensor when acquiring livestock and poultry activity data can be automatically obtained through a built-in time synchronization mechanism, or it can be obtained in other ways, which are not limited or elaborated on in detail.

[0076] It should be noted that when the acquisition time fluctuation coefficient is larger, the possibility of sensor errors in obtaining livestock and poultry activity data is greater, and the possibility of inconsistency between the livestock and poultry activity data obtained by the sensor and the actual livestock and poultry activity data is also greater. If it is still uploaded to the cloud or local server, it may cause errors in the analyzed health status and behavior patterns of livestock and poultry, leading to farmers making wrong decision support. The reason is that when the acquisition time fluctuation coefficient is larger, it means that there is a large time interval fluctuation of the sensor during the data collection process, which means that the frequency and timeliness of data collection are unstable. When the interval between timestamps fluctuates greatly, the interval of data collection is inconsistent, which may lead to a large time error between data at different time points, so that the obtained livestock and poultry activity data does not match the time series of actual activities. This inconsistency may affect the accuracy of the data, and then lead to erroneous analysis of health status and behavior patterns. If these erroneous data are uploaded directly to the cloud or local server without correction, the data analysis system will make decisions based on inaccurate data, which may lead to erroneous health assessments or behavior predictions. The result may be wrong intervention measures or management strategies, which will affect farmers' decisions, cause unnecessary waste of resources, and even affect the health and breeding efficiency of livestock and poultry.

[0077] In one implementation, the benefit of analyzing the collection time fluctuation coefficient for determining whether the livestock and poultry activity data obtained by the sensor can monitor the health status and behavior patterns of livestock and poultry is that the collection time fluctuation coefficient can effectively reflect the regularity and stability of data collection. When the fluctuation coefficient is small, it means that the collection interval of the sensor is relatively uniform and the time stability of data collection is high, thereby ensuring the consistency and comparability of the data in time, which provides a reliable basis for subsequent health monitoring and behavior pattern analysis. When the fluctuation coefficient is large, it reflects the instability in the collection process, which may cause the time interval confusion during data collection, thereby affecting the accurate monitoring of livestock and poultry activities. By monitoring this fluctuation coefficient, potential sensor problems or data quality problems can be discovered in a timely manner, so that effective corrections or interventions can be made to ensure that the monitoring system can provide accurate and real-time health status assessment and behavior prediction, helping farmers make more scientific and accurate decisions.

[0078] In one embodiment, calculating the data unqualified coefficient according to the electromagnetic interference coefficient, the temperature and humidity influence coefficient, and the acquisition time fluctuation coefficient includes:

[0079]

[0080] In the formula, is the data failure coefficient, , , They are electromagnetic interference coefficient, temperature and humidity influence coefficient, and collection time fluctuation coefficient. They are , , The preset scaling factor of Both are greater than 0.

[0081] It should be noted that It is set by professionals according to the actual situation. Generally, The sum of is 1, for example It can be 0.2, 0.4, 0.4 respectively; it can also be other numbers, and there is no specific limitation; in addition, before calculating the data unqualified coefficient, it is necessary to remove the unit of the electromagnetic interference coefficient, the temperature and humidity influence coefficient and the collection time fluctuation coefficient;

[0082] In one embodiment, judging whether the health status and behavior pattern of livestock and poultry can be monitored through livestock and poultry activity data obtained by sensors according to the data unqualified coefficient and the preset data unqualified coefficient threshold includes:

[0083] If the data unqualified coefficient is less than the preset data unqualified coefficient threshold, the health status and behavior pattern of the livestock and poultry can be monitored through the livestock and poultry activity data obtained by the sensor;

[0084] If the data unqualified coefficient is not less than the preset data unqualified coefficient threshold, the health status and behavior patterns of livestock and poultry cannot be monitored through the livestock and poultry activity data obtained by the sensor; an alarm signal is issued at this time.

[0085] It should be noted that the preset data unqualified coefficient threshold is set by professionals based on actual conditions and is not limited or elaborated on in detail.

[0086] It should be noted that if the data failure coefficient is less than the preset data failure coefficient threshold, it means that the livestock and poultry activity data collected by the sensor are less affected by electromagnetic interference, temperature and humidity changes, and collection time fluctuations, and the data accuracy and stability are high. Therefore, it can be considered that these data can reflect the true health status and behavior patterns of livestock and poultry, and then effectively monitor and analyze them through these data. In this case, the quality of the data meets the monitoring requirements and can provide valuable decision support for farmers, helping to implement precise management and early warning.

[0087] However, if the data failure coefficient is not less than the preset data failure coefficient threshold, it means that the sensor has been greatly disturbed during the data collection process, and there may be large errors or instability. In this case, the obtained livestock and poultry activity data deviates greatly from the actual situation and cannot accurately reflect the health status and behavior patterns of livestock and poultry. If such data continues to be uploaded and used for analysis, it may lead to incorrect health assessments and behavior predictions, thereby affecting the decision-making effect of breeding management. To avoid this situation, the system will issue an alarm signal to indicate that the sensor may have a fault or data quality problem, requiring relevant personnel to check and adjust in time to ensure the accuracy of subsequent data collection and the effectiveness of monitoring.

[0088] Based on the same inventive concept, the present invention also provides a data monitoring system for livestock and poultry activities. Figure 2 , Figure 2 A framework diagram of a data monitoring system for livestock and poultry activities provided by an embodiment of the present invention, the system comprising:

[0089] Electromagnetic interference module: collects electromagnetic interference signals from the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculates the electromagnetic interference coefficient based on the electromagnetic interference signals;

[0090] Temperature and humidity impact module: collects the temperature and humidity of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculates the temperature and humidity impact coefficient based on the temperature and humidity;

[0091] Collection time fluctuation module: collects the data collection timestamp when the sensor acquires livestock and poultry activity data, and calculates the collection time fluctuation coefficient based on the data collection timestamp;

[0092] Monitoring module: Calculate the data unqualified coefficient based on the electromagnetic interference coefficient, temperature and humidity influence coefficient and collection time fluctuation coefficient, and determine whether the health status and behavior patterns of livestock and poultry can be monitored through the livestock and poultry activity data obtained by the sensor based on the data unqualified coefficient and the preset data unqualified coefficient threshold.

[0093] Based on a data monitoring system for livestock and poultry activities provided by an embodiment of the present invention, through the above method, in the actual data monitoring of livestock and poultry activities, it is possible to judge whether the data of livestock and poultry activities obtained by the sensor is consistent with the actual data of livestock and poultry activities, and respond in a timely manner to ensure that the health status and behavior patterns of the analyzed livestock and poultry are correct and in line with reality, so as to support farmers in making correct decisions.

[0094] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be used to artificially limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A data monitoring method for livestock and poultry activities, characterized in that: The following steps are involved: Collect electromagnetic interference signals of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculate the electromagnetic interference coefficient based on the electromagnetic interference signals; Collect the temperature and humidity of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculate the temperature and humidity influence coefficient based on the temperature and humidity; Collect the data acquisition timestamp when the sensor acquires livestock and poultry activity data, and calculate the acquisition time fluctuation coefficient based on the data acquisition timestamp; The data unqualified coefficient is calculated according to the electromagnetic interference coefficient, the temperature and humidity influence coefficient and the collection time fluctuation coefficient, and it is judged whether the health status and behavior pattern of livestock and poultry can be monitored through the livestock and poultry activity data obtained by the sensor according to the data unqualified coefficient and the preset data unqualified coefficient threshold; Calculating the electromagnetic interference coefficient based on the electromagnetic interference signal includes: The time interval during which the sensor obtains livestock and poultry activity data is recorded as the target time interval, and the electromagnetic interference signal of the sensor in the target time interval is obtained and marked as ,in, , is a positive integer, Indicates the number of electromagnetic interference signals; use Wavelet basis function for each electromagnetic interference signal obtained Perform continuous wavelet transform. , the electromagnetic interference signal is decomposed in the time domain and frequency domain, as follows: ; In the formula, are the wavelet coefficients, It is an electromagnetic interference signal. is the selected wavelet basis function, is the scale parameter, which is used to adjust the scale of the wavelet basis function; is the translation parameter, which is used to adjust the position of the wavelet basis function; Represents the time coordinate of the signal, that is, the position on the time axis; Extract the energy characteristics of the wavelet coefficients. According to the calculated wavelet coefficients, further extract the energy characteristics and calculate the energy of the wavelet coefficients at each scale. The calculation formula is as follows: ; In the formula, is in scale The energy below is the wavelet coefficient, and then the energy of the wavelet coefficients at different scales is summed to obtain the comprehensive energy characteristics ; Calculate the electromagnetic interference index of each electromagnetic interference signal, and the calculation expression is: , where is the electromagnetic interference index; All electromagnetic interference index Add them together to get the electromagnetic interference coefficient, and the calculation formula is: , where is the electromagnetic interference coefficient.

2. A method for monitoring livestock and poultry activities according to claim 1, characterized in that: Calculation of temperature and humidity influence coefficients based on temperature and humidity includes: The time interval when the sensor obtains livestock and poultry activity data is recorded as the target time interval, and the temperature and humidity of the environment where the sensor is located in the target time interval are obtained. The temperature and humidity influence coefficient is calculated according to the temperature and humidity of the environment. The calculation formula is: in, is the temperature and humidity influence coefficient, , Respectively represent the temperature and humidity of the environment, [ , ] indicates the time period when the ambient temperature is outside the preset effective operating temperature range of the sensor. [ , ] indicates the time period when the humidity of the environment is outside the preset effective working humidity range of the sensor; and are the preset proportional coefficients for temperature and humidity, respectively, and and Both are greater than 0.

3. A method for monitoring livestock and poultry activities according to claim 1, characterized in that: Calculating the collection time fluctuation coefficient based on the data collection timestamp includes: The time interval in which the sensor obtains livestock and poultry activity data is recorded as the target time interval, and the data acquisition timestamp in the target time interval is obtained to obtain a timestamp sequence based on time order; Calculate the time interval between every two adjacent time stamps in the time stamp sequence as the response time interval, and obtain a response interval sequence based on the time order; The response interval in the response interval sequence is calibrated as , Indicates the order number of the response interval in the response interval sequence, , is the total number of response intervals in the response interval sequence, and is a positive integer; Calculate the mean of the response interval series. The calculation formula is: ,in, is the mean of the response interval series; Calculate the acquisition time fluctuation coefficient, the calculation formula is: ,in, is the acquisition time fluctuation coefficient.

4. A method for monitoring livestock and poultry activities according to claim 1, characterized in that: The data failure coefficients calculated based on the electromagnetic interference coefficient, temperature and humidity influence coefficient, and acquisition time fluctuation coefficient include: In the formula, is the data failure coefficient, , , They are electromagnetic interference coefficient, temperature and humidity influence coefficient, and collection time fluctuation coefficient. They are , , The preset scaling factor of Both are greater than 0.

5. The method for data monitoring of livestock and poultry activities according to claim 1, characterized in that: According to the data unqualified coefficient and the preset data unqualified coefficient threshold, it is judged whether the health status and behavior pattern of livestock and poultry can be monitored through the livestock and poultry activity data obtained by the sensor, including: If the data unqualified coefficient is less than the preset data unqualified coefficient threshold, the health status and behavior pattern of the livestock and poultry can be monitored through the livestock and poultry activity data obtained by the sensor; If the data unqualified coefficient is not less than the preset data unqualified coefficient threshold, the health status and behavior patterns of livestock and poultry cannot be monitored through the livestock and poultry activity data obtained by the sensor; an alarm signal is issued at this time.

6. A data monitoring system for livestock and poultry activities, used to implement a data monitoring method for livestock and poultry activities as described in any one of claims 1 to 5, characterized in that: The system comprises: Electromagnetic interference module: collects electromagnetic interference signals from the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculates the electromagnetic interference coefficient based on the electromagnetic interference signals; Temperature and humidity impact module: collects the temperature and humidity of the environment in which the sensor is located when acquiring livestock and poultry activity data, and calculates the temperature and humidity impact coefficient based on the temperature and humidity; Collection time fluctuation module: collects the data collection timestamp when the sensor acquires livestock and poultry activity data, and calculates the collection time fluctuation coefficient based on the data collection timestamp; Monitoring module: Calculate the data unqualified coefficient based on the electromagnetic interference coefficient, temperature and humidity influence coefficient and collection time fluctuation coefficient, and determine whether the health status and behavior patterns of livestock and poultry can be monitored through the livestock and poultry activity data obtained by the sensor based on the data unqualified coefficient and the preset data unqualified coefficient threshold.

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