A method, system and medium for collecting livestock farming environment data

Abstract

This invention relates to the technical field and proposes a method, system, and medium for collecting livestock farming environmental data. The method includes: analyzing the impact of other dimensions of environmental data in a periodic multidimensional environmental data sequence on changes in ammonia and carbon dioxide concentrations in the monitored area to obtain the degree of manure fermentation impact in the monitored area at the current moment; obtaining the manure impact attention level in the monitored area at the current moment based on the degree of manure fermentation impact and the degree of manure accumulation; assigning attention weights to different monitored areas based on the environmental quality attention level, animal quantity, and total weight to obtain the comprehensive environmental quality attention level at the current moment; obtaining the collection frequency adjustment coefficient for the next cycle in the farm based on the comprehensive environmental quality attention level; and adaptively adjusting the collection frequency of environmental data in the farm for the next cycle based on the collection frequency adjustment coefficient. This invention improves the efficiency and effectiveness of livestock farming environmental data collection.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically to a method, system, and medium for collecting data on livestock farming environment. Background Technology

[0002] With the rapid development of animal husbandry, refined management has become an important means to improve breeding efficiency and animal health. The breeding environment has a direct impact on animal growth, reproduction, and the immune system; therefore, the accurate collection and management of breeding environment data is particularly important. In recent years, with the continuous advancement of Internet of Things (IoT) and sensor technologies, the application of environmental monitoring systems in animal husbandry has gradually become widespread.

[0003] Traditional environmental data acquisition methods mostly employ static, fixed-frequency data collection, neglecting the accumulation and cleanup of animal manure in the farming environment. If manure is not removed promptly or thoroughly, it will accumulate and ferment, producing harmful gases that severely impact the environmental quality of the farm. Furthermore, static, fixed-frequency data collection methods cannot dynamically adjust based on manure accumulation and fermentation, leading to high-frequency data collection even when environmental quality is good, increasing storage and transmission costs. In the event of sudden changes in environmental quality, critical data points may be missed, delaying early warnings. Summary of the Invention

[0004] This invention provides a method, system, and medium for collecting livestock farming environmental data. It addresses the problem that static, fixed-frequency data collection methods cannot dynamically adjust based on manure accumulation and fermentation, leading to high-frequency data collection even when environmental quality is good, increasing storage and transmission costs. Furthermore, it suggests that during periods of sudden environmental quality changes, critical data points may be missed, delaying early warnings. The specific technical solution adopted is as follows:

[0005] This invention proposes a method for collecting environmental data in livestock farming, which includes the following steps:

[0006] Acquire periodic multidimensional environmental data sequences for several monitoring areas within the farm, as well as the number and total weight of animals; the multidimensional environmental data includes: ammonia concentration, carbon dioxide concentration, temperature data, humidity data, and light intensity;

[0007] By analyzing the changes in ammonia and carbon dioxide concentrations in the periodic multidimensional environmental data series of the monitoring area, the degree of fecal accumulation in the monitoring area at the current moment is obtained; by analyzing the influence of other dimensions of environmental data on the changes in ammonia and carbon dioxide concentrations, the degree of fecal fermentation impact in the monitoring area at the current moment is obtained; based on the degree of fecal fermentation impact and the degree of fecal accumulation, the level of concern regarding the impact of feces in the monitoring area at the current moment is obtained.

[0008] Based on the differences in the level of concern about the impact of feces between the monitoring area and surrounding monitoring areas, the environmental quality concern level of each monitoring area at the current moment is obtained; by analyzing the environmental quality concern level, animal number and total weight of different monitoring areas, a concern weight is assigned to different monitoring areas to obtain the comprehensive environmental quality concern level at the current moment; based on the comprehensive environmental quality concern level, the sampling frequency adjustment coefficient for the next cycle in the farm is obtained;

[0009] The frequency of environmental data collection in the farm for the next cycle is adaptively adjusted based on the collection frequency adjustment coefficient.

[0010] Preferably, the method for obtaining the degree of fecal accumulation in the monitoring area at the current moment by analyzing the changes in ammonia and carbon dioxide concentrations in the periodic multidimensional environmental data sequence of the monitoring area includes:

[0011] In the periodic multidimensional environmental data sequence of the monitoring area, all sampling times before the current time are recorded as historical times;

[0012] The least squares method was used to fit curves of ammonia and carbon dioxide concentration data of the monitoring area at all historical times, so as to obtain the ammonia and carbon dioxide change curves of the monitoring area at the current time.

[0013] The ratio between the ammonia concentration data of the monitoring area at the current moment and the maximum ammonia concentration data value in the ammonia change curve of the monitoring area at the current moment is recorded as the first fecal maximum accumulation factor; the ratio between the carbon dioxide concentration data of the monitoring area at the current moment and the maximum carbon dioxide concentration data value in the carbon dioxide change curve of the monitoring area at the current moment is recorded as the second fecal maximum accumulation factor; the average of the first fecal maximum accumulation factor and the second fecal maximum accumulation factor is taken as the fecal accumulation degree of the monitoring area at the current moment.

[0014] Preferably, the method for obtaining the degree of influence of fecal fermentation in the monitoring area at the current moment by analyzing the impact of changes in ammonia and carbon dioxide concentrations through other dimensions of environmental data includes:

[0015] Temperature data, humidity data, and light intensity are all recorded as influencing data;

[0016] The mean of the standard deviations of ammonia and carbon dioxide concentration data for the monitoring area at all historical moments is recorded as the gas fluctuation amplitude of the monitoring area at the current moment; the... The gas fluctuation amplitude of the monitored area at the first historical moment and the first The absolute value of the difference between the gas fluctuation amplitudes of the monitored area at each historical moment is denoted as the nth. The gas fluctuation changes in the monitoring area at each historical moment; the sequence of gas fluctuation changes in the monitoring area at all historical moments is denoted as the gas fluctuation change sequence of the monitoring area at the current moment.

[0017] The monitoring area at all historical moments The standard deviation of the impact data of each dimension is denoted as the first standard deviation of the monitored area at the current time. The impact of each dimension on the fluctuation range of the data; The monitoring area at the first historical moment The fluctuation range of the impact data of the first dimension and the second dimension The monitoring area at the first historical moment The absolute value of the difference between the fluctuation amplitudes of the data in each dimension is denoted as the _th_. The monitoring area at the first historical moment The fluctuation and change of data in each dimension; the first dimension of the monitoring area at all historical moments. The sequence of fluctuations in the data across various dimensions is denoted as the first (i) of the monitored area at the current moment. The sequence of fluctuations in data influenced by various dimensions;

[0018] The mean of the Pearson correlation coefficients between the gas fluctuation change sequence of the monitoring area at the current moment and the fluctuation change sequences of all dimensions of influence data in the monitoring area at the current moment is taken as the degree of influence of fecal fermentation in the monitoring area at the current moment.

[0019] Preferably, the method for obtaining the level of concern regarding the impact of fecal fermentation and the degree of fecal accumulation in the monitoring area at the current moment includes:

[0020] The normalized value of the product of the degree of fecal fermentation impact in the monitored area at the current moment and the cumulative degree of fecal matter in the monitored area at the current moment is taken as the fecal impact concern level in the monitored area at the current moment.

[0021] Preferably, the method for obtaining the environmental quality concern level of each monitoring area at the current moment based on the difference in concern level regarding the impact of feces between the monitoring area and surrounding monitoring areas includes:

[0022] Preset a neighborhood parameter , obtain the The distance between the center of each monitoring area and the center of all other monitoring areas; the nearest front Each of the monitoring areas is considered as the first monitoring area. Adjacent monitoring areas of each monitoring area;

[0023] According to the The monitoring area and the first The differences in distance and fecal impact concern between adjacent monitoring areas were obtained to determine the first... The monitoring area and the first The degree of gas diffusion impact between adjacent monitoring areas;

[0024] The current moment is the next The sum of the gas diffusion influence between the current monitoring area and all adjacent monitoring areas is denoted as the first sum; the first sum is then compared with the sum of the gas diffusion influence between the current monitoring area and all adjacent monitoring areas. The normalized value of the product of the public's concern about the impact of feces on each monitoring area is used as the value of the first monitoring area at the current moment. Environmental quality concerns in each monitoring area.

[0025] Preferably, the method according to the first The monitoring area and the first The differences in distance and fecal impact concern between adjacent monitoring areas were obtained to determine the first... The monitoring area and the first The degree of gas diffusion influence between adjacent monitoring areas includes the following specific methods:

[0026] The current moment is the next The level of concern regarding the impact of feces in the monitoring areas is comparable to that of the first monitoring area. The first monitoring area The absolute value of the difference between the level of concern regarding the impact of feces on adjacent monitoring areas is denoted as the first absolute value of the difference; the first absolute value of the difference is compared with the first absolute value of the difference. The monitoring area and the first The ratio of the distances between the centers of adjacent monitoring areas is used as the ratio of the distances between the centers of adjacent monitoring areas at the current time. The monitoring area and the first The degree of gas diffusion impact between adjacent monitoring areas.

[0027] Preferably, the method for obtaining the comprehensive environmental quality attention level at the current moment by analyzing the environmental quality attention level, animal quantity, and total weight of different monitoring areas and assigning attention weights to different monitoring areas is as follows:

[0028] The current location of the center of each monitoring area, the environmental quality concern, the number of animals and the total weight are used as the feature vector of each monitoring area. Based on the Euclidean distance between the feature vectors of the monitoring areas, the DBSCAN clustering algorithm is used to cluster all monitoring areas in the farm to obtain several clusters.

[0029] The first In the cluster, the th The product of the number of animals and their total weight in each monitoring area is denoted as the i-th. Animal impact factors in the monitoring area; the first Animal impact factors in the first monitoring area and the first The ratio of the area of ​​each monitoring area is denoted as the th monitoring area. The regional impact factor of the monitoring area; will the first The regional impact factor of each monitoring area and the current time of the [missing information] The product of the environmental quality concerns of each monitoring area is denoted as the product of the environmental quality concerns at the current time. Environmental quality focus weight for each monitoring area;

[0030] The first The normalized value of the sum of the environmental quality concern weights of all monitored areas in each cluster at the current time is used as the value of the i-th cluster at the current time. The degree of local accumulation of harmful gases in each cluster;

[0031] The average degree of local accumulation of harmful gases in all clusters at the current moment is taken as the overall environmental quality concern at the current moment.

[0032] Preferably, the specific method for obtaining the sampling frequency adjustment coefficient for the next cycle within the farm based on comprehensive environmental quality concern is as follows:

[0033] Using the current level of public concern about the overall environmental quality as a weight, the ammonia concentration data at the current moment is input into the weighted prediction algorithm to obtain the ammonia concentration data sequence for the next cycle in the farm.

[0034] Preset a normal ammonia concentration threshold The mean of all ammonia concentration data in the next cycle of the ammonia concentration data series in the farm is compared with the normal ammonia concentration threshold. The ratio between them is used as the sampling frequency adjustment coefficient for the next cycle in the farm.

[0035] The present invention also proposes a livestock farming environment data acquisition system, which includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the above method.

[0036] This invention also proposes a livestock farming environment data acquisition medium, which includes:

[0037] The system includes a data acquisition module, a data acquisition frequency adjustment coefficient acquisition module, and a data acquisition frequency adjustment module. The data acquisition module is used to acquire periodic multidimensional environmental data sequences of several monitoring areas within the farm, as well as the number and total weight of animals. The data acquisition frequency adjustment coefficient acquisition module obtains the data acquisition frequency adjustment coefficient for the next period within the farm by calling a computer program to implement the steps of the above method. The data acquisition frequency adjustment module adaptively adjusts the data acquisition frequency of the environmental data for the next period within the farm based on the data acquisition frequency adjustment coefficient.

[0038] The beneficial effects of this invention are as follows: This invention analyzes the impact of environmental data from other dimensions in the periodic multidimensional environmental data sequence of the monitoring area on changes in ammonia and carbon dioxide concentrations to obtain the degree of impact of fecal fermentation in the monitoring area at the current moment; based on the degree of impact of fecal fermentation and the degree of fecal accumulation, it obtains the fecal impact attention level of the monitoring area at the current moment; by analyzing the environmental quality attention level, animal quantity, and total weight of different monitoring areas, it assigns attention weights to different monitoring areas to obtain the comprehensive environmental quality attention level at the current moment; based on the comprehensive environmental quality attention level, it obtains the sampling frequency adjustment coefficient for the next cycle in the farm; based on the sampling frequency adjustment coefficient, it adaptively adjusts the sampling frequency of environmental data in the next cycle in the farm; by comprehensively considering the fecal impact attention level and environmental quality attention factors, it can more comprehensively assess the comprehensive environmental quality of the farm; this helps to discover potential problems in farm environmental management, adjust the farming environment in a timely manner, thereby improving animal health and improving the overall production efficiency of the farm; by adaptively adjusting the sampling frequency of environmental data, the sampling frequency can be increased at critical moments (such as when ammonia concentration fluctuates greatly) to capture more environmental change data; while the sampling frequency can be reduced when the environment is stable, saving resources and avoiding data redundancy. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart illustrating the steps of a livestock farming environment data collection method according to the present invention.

[0041] Figure 2 This is a flowchart illustrating the characteristic relationships of a livestock farming environment data collection method according to the present invention. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Please see Figure 1 The diagram illustrates a flowchart of a livestock farming environment data acquisition method according to an embodiment of the present invention, which includes the following steps:

[0044] Step S001: Obtain periodic multidimensional environmental data sequences for several monitoring areas within the farm, as well as the number and total weight of animals; the multidimensional environmental data includes: ammonia concentration, carbon dioxide concentration, temperature data, humidity data, and light intensity.

[0045] It should be noted that this embodiment is illustrated using an hourly cycle as an example. The environmental data of the farm in the next cycle is predicted by using the environmental data of the farm in the previous historical time. Then, the collection frequency of the farm in the next cycle is adjusted. The environmental data of the farm in the next cycle is collected again using the adjusted collection frequency. This process is repeated to obtain an adaptive adjustment of the collection frequency of the environmental data of the farm in each subsequent cycle.

[0046] Specifically, the methods for collecting periodic multidimensional environmental data sequences from several monitoring areas within the farm, as well as the number and total weight of animals, are as follows:

[0047] Based on the sex and age of the animals in the farm, the livestock farm is divided into several monitoring areas, such as an area for adult male animals, an area for adult female animals, an area for juvenile animals, and an area for mixed rearing of adult female animals and juvenile animals. Sensors of the corresponding types for temperature, humidity, ammonia concentration, carbon dioxide concentration, and light intensity are placed in the center of each monitoring area, and the data collected by the sensors are normalized using the Z-Score normalization algorithm.

[0048] For any given monitoring area, a sampling time is defined as every minute. Each time, multiple types of sensors are used to sequentially collect five data types from the farm: temperature, humidity, ammonia concentration, carbon dioxide concentration, and light intensity. The data collection lasts for one hour. The sequence of temperature, humidity, ammonia concentration, carbon dioxide concentration, and light intensity data from all sampling times is recorded as the periodic multidimensional environmental data sequence for the given monitoring area.

[0049] The Z-Score standardization algorithm is an existing technology, and will not be described in detail here.

[0050] Thus, periodic multidimensional environmental data sequences for several monitoring areas within the farm, as well as the number and total weight of animals, were obtained.

[0051] Step S002: By analyzing the changes in ammonia and carbon dioxide concentrations in the periodic multidimensional environmental data sequence of the monitoring area, the degree of fecal accumulation in the monitoring area at the current moment is obtained; by analyzing the influence of other dimensions of environmental data on the changes in ammonia and carbon dioxide concentrations, the degree of fecal fermentation influence in the monitoring area at the current moment is obtained; based on the degree of fecal fermentation influence and the degree of fecal accumulation, the fecal impact attention level in the monitoring area at the current moment is obtained.

[0052] It should be noted that animal manure in farms accumulates over time and is then manually treated. During this accumulation and cleaning process, changes in ammonia and carbon dioxide concentrations within the farm reflect the extent of manure accumulation. If manure is not removed promptly or completely, it can lead to fermentation. Temperature, humidity, and light intensity within the farm can all influence manure fermentation. Therefore, by analyzing changes in ammonia and carbon dioxide concentrations, we can obtain the current manure accumulation status in each monitoring area of ​​the farm. Further analysis of the impact of other environmental data on manure fermentation allows us to determine the current level of concern regarding the impact of manure on each monitoring area of ​​the farm.

[0053] This embodiment uses any monitoring area as an example for illustration:

[0054] Preferably, in one embodiment of the present invention, since animal feces naturally decompose during accumulation, producing ammonia and carbon dioxide, the concentration changes of these two gases should be proportional to the amount of feces accumulated. Therefore, an increase in concentration may indicate a greater accumulation of feces. Thus, the specific method for obtaining the degree of feces accumulation in the monitoring area at the current moment by analyzing the changes in ammonia and carbon dioxide concentrations in the periodic multidimensional environmental data sequence of the monitoring area is as follows:

[0055] In the periodic multidimensional environmental data sequence of the monitoring area, all sampling times before the current time are recorded as historical times;

[0056] The least squares method was used to fit curves of ammonia and carbon dioxide concentration data of the monitoring area at all historical times, so as to obtain the ammonia and carbon dioxide change curves of the monitoring area at the current time.

[0057] The ratio between the ammonia concentration data of the monitoring area at the current moment and the maximum ammonia concentration data value in the ammonia change curve of the monitoring area at the current moment is recorded as the first fecal maximum accumulation factor; the ratio between the carbon dioxide concentration data of the monitoring area at the current moment and the maximum carbon dioxide concentration data value in the carbon dioxide change curve of the monitoring area at the current moment is recorded as the second fecal maximum accumulation factor; the average of the first fecal maximum accumulation factor and the second fecal maximum accumulation factor is taken as the fecal accumulation degree of the monitoring area at the current moment.

[0058] Preferably, in one embodiment of the present invention, the fluctuation range of ammonia concentration data and carbon dioxide concentration data can reflect whether the accumulation and removal of feces in the monitoring area are within a stable range over all historical time periods. If the fluctuation of these two dimensions of environmental data is large, it may mean that the feces in the monitoring area of ​​the farm are not removed in a timely manner or are not completely removed, leading to the accumulation and fermentation of feces, which increases the fluctuation of ammonia concentration data and carbon dioxide concentration data. Moreover, since temperature data, humidity data, and light intensity in the farm all affect the fermentation of feces, a sudden increase or decrease in the fluctuation range of ammonia concentration data and carbon dioxide concentration data will also be reflected in the three dimensions of environmental data: temperature data, humidity data, and light intensity. That is, an increase in temperature data, humidity data, and light intensity will enhance the fermentation of feces, resulting in the production of more ammonia and carbon dioxide. Therefore, the specific method for obtaining the degree of influence of fecal fermentation in the monitoring area at the current time by analyzing the influence of other dimensions of environmental data in the periodic multidimensional environmental data sequence of the monitoring area on the changes in ammonia concentration and carbon dioxide concentration is as follows:

[0059] Temperature data, humidity data, and light intensity are all recorded as influencing data;

[0060] The mean of the standard deviations of ammonia and carbon dioxide concentration data for the monitoring area at all historical moments is recorded as the gas fluctuation amplitude of the monitoring area at the current moment; the... The gas fluctuation amplitude of the monitored area at the first historical moment and the first The absolute value of the difference between the gas fluctuation amplitudes of the monitored area at each historical moment is denoted as the nth. The gas fluctuation changes in the monitoring area at each historical moment; the sequence of gas fluctuation changes in the monitoring area at all historical moments is denoted as the gas fluctuation change sequence of the monitoring area at the current moment.

[0061] The monitoring area at all historical moments The standard deviation of the impact data of each dimension is denoted as the first standard deviation of the monitored area at the current time. The impact of each dimension on the fluctuation range of the data; The monitoring area at the first historical moment The fluctuation range of the impact data of the first dimension and the second dimension The monitoring area at the first historical moment The absolute value of the difference between the fluctuation amplitudes of the data in each dimension is denoted as the _th_. The monitoring area at the first historical moment The fluctuation and change of data in each dimension; the first dimension of the monitoring area at all historical moments. The sequence of fluctuations in the data across various dimensions is denoted as the first (i) of the monitored area at the current moment. The sequence of fluctuations in data influenced by various dimensions;

[0062] It should be noted that when there is a strong correlation between the fluctuation sequence of a certain dimension of the impact data and the gas fluctuation sequence, it can be inferred that the manure in the monitored area of ​​the farm was not removed in a timely manner or was not completely removed, resulting in the accumulation and fermentation of manure, which caused fluctuations in the ammonia and carbon dioxide concentration data.

[0063] The mean of the Pearson correlation coefficients between the gas fluctuation change sequence of the monitoring area at the current moment and the fluctuation change sequences of all dimensions of influence data in the monitoring area at the current moment is taken as the degree of influence of fecal fermentation in the monitoring area at the current moment.

[0064] Among them, the Pearson correlation coefficient and the least squares method are existing technologies, and will not be described in detail here.

[0065] Preferably, in one embodiment of the present invention, the higher the degree of impact of fecal fermentation, the greater the fluctuations in ammonia and carbon dioxide concentration data in the monitoring area of ​​the farm, indicating that the untreated feces have fermented due to the influence of other environmental data. Therefore, it is more important to pay attention to the amount of animal feces in the monitoring area at the current moment. Thus, the specific method for obtaining the degree of concern regarding the impact of fecal fermentation and the degree of fecal accumulation in the monitoring area at the current moment is as follows:

[0066] The normalized value of the product of the degree of fecal fermentation impact in the monitored area at the current moment and the cumulative degree of fecal impact in the monitored area at the current moment is taken as the fecal impact concern level in the monitored area at the current moment.

[0067] The specific formula is as follows:

[0068]

[0069] In the formula, This indicates the level of public concern regarding the impact of feces on the monitored area at the current moment. This indicates the current level of fecal accumulation in the monitored area. This indicates the degree of impact of fecal fermentation in the monitored area at the current moment; This represents the linear normalization function.

[0070] This gives us the current level of concern regarding the impact of feces on each monitoring area.

[0071] Step S003: Based on the differences in the level of concern about the impact of feces between the monitoring area and the surrounding monitoring areas, obtain the environmental quality concern level of each monitoring area at the current moment; by analyzing the environmental quality concern level, the number of animals, and the total weight of different monitoring areas, assign concern weights to different monitoring areas to obtain the comprehensive environmental quality concern level at the current moment; based on the comprehensive environmental quality concern level, obtain the sampling frequency adjustment coefficient for the next cycle in the farm.

[0072] It should be noted that because the age and number of animals raised in different monitoring areas within a farm vary, the amount of feces produced will differ, resulting in differences in the level of concern regarding the impact of feces. This is visually manifested as an uneven distribution of feces accumulation. If the level of concern regarding the impact of feces is high in adjacent monitoring areas within the farm at any given time, it indicates that the amount of accumulated feces and the fermentation process in adjacent monitoring areas are significant. This would make it difficult for ammonia, which produces toxic gases, to disperse, thus seriously affecting the environmental quality within the farm at that time. Therefore, it is necessary to strengthen the monitoring of the environmental quality at that moment.

[0073] Preferably, in one embodiment of the present invention, the first The greater the level of concern regarding the impact of feces in a monitoring area, the more significant the impact. If the amount of accumulated feces in a monitoring area is large and the fermentation of feces is severe, a large amount of toxic ammonia gas will be produced; if the first... The smaller the difference in the level of concern regarding the impact of feces between a monitoring area and its adjacent monitoring areas, the more similar the accumulated amount and fermentation status of feces in these two adjacent monitoring areas. This would prevent the effective diffusion of toxic ammonia gas, leading to the accumulation of ammonia gas in these monitoring areas, which could threaten animal health. The greater the difference in the level of concern regarding the impact of feces between a monitoring area and its adjacent areas, the greater the difference in the amount of feces accumulated and the fermentation status between the adjacent monitoring areas; at this time, the toxic gas ammonia produced can be dispersed more effectively, thereby reducing the gas concentration in the local area and helping to reduce harm; thus, it will seriously affect the environmental quality within the farm at the current moment; and the first The closer a monitoring area is to its neighboring monitoring areas, the greater its impact on the diffusion of ammonia, a toxic gas produced after fecal fermentation. Therefore, based on the differences in the level of concern regarding the impact of feces between each monitoring area and its surrounding areas, the specific method for obtaining the environmental quality concern level of each monitoring area at the current moment is as follows:

[0074] Preset a neighborhood parameter In this embodiment, This example is used for illustration; no specific limitations are set in this embodiment. It depends on the specific implementation situation;

[0075] Get the The distance between the center of each monitoring area and the center of all other monitoring areas; the nearest front Each of the monitoring areas is considered as the first monitoring area. Adjacent monitoring areas of each monitoring area;

[0076] The current moment is the next The level of concern regarding the impact of feces in the monitoring areas is comparable to that of the first monitoring area. The first monitoring area The absolute value of the difference between the level of concern regarding the impact of feces on adjacent monitoring areas is denoted as the first absolute value of the difference; the first absolute value of the difference is compared with the first absolute value of the difference. The monitoring area and the first The ratio of the distances between the centers of adjacent monitoring areas is used as the ratio of the distances between the centers of adjacent monitoring areas at the current time. The monitoring area and the first The degree of gas diffusion impact between adjacent monitoring areas;

[0077] The specific formula is as follows:

[0078]

[0079] In the formula, Indicates the next time step. The monitoring area and the first The degree of gas diffusion impact between adjacent monitoring areas; Indicates the next time step. The impact of fecal matter in each monitoring area on public awareness; Indicates the next time step. The first monitoring area The impact of fecal matter from adjacent monitoring areas on public awareness; Indicates the first The monitoring area and the first The distance between the centers of adjacent monitoring areas; This indicates taking the absolute value.

[0080] The current moment is the next The sum of the gas diffusion influence between the current monitoring area and all adjacent monitoring areas is denoted as the first sum; the first sum is then compared with the sum of the gas diffusion influence between the current monitoring area and all adjacent monitoring areas. The normalized value of the product of the public's concern about the impact of feces on each monitoring area is used as the value of the first monitoring area at the current moment. Environmental quality concerns in each monitoring area;

[0081] The specific formula is as follows:

[0082]

[0083] In the formula, Indicates the next time step. Environmental quality concerns in each monitoring area; Indicates the next time step. The impact of fecal matter in each monitoring area on public awareness; Indicates the first The number of all adjacent monitoring areas of a monitoring area; Indicates the next time step. The monitoring area and the first The degree of gas diffusion impact between adjacent monitoring areas; This represents the linear normalization function.

[0084] Preferably, in one embodiment of the present invention, since the greater the number and total weight of animals in different monitoring areas within the farm, the greater the impact of feces production, and thus the greater the environmental quality concern; and since the amount of feces produced by young and old animals also differs, that is, adult animals may produce more feces, while immature animals produce relatively less feces; therefore, the specific method for obtaining the comprehensive environmental quality concern at the current moment by analyzing the environmental quality concern, the number of animals, and the total weight in different monitoring areas and assigning concern weights to different monitoring areas is as follows:

[0085] The current location of the center of each monitoring area, the environmental quality concern, the number of animals and the total weight are used as the feature vector of each monitoring area. Based on the Euclidean distance between the feature vectors of the monitoring areas, the DBSCAN clustering algorithm is used to cluster all monitoring areas in the farm to obtain several clusters.

[0086] In this embodiment, for any given cluster, if the area of ​​the cluster is smaller, the number and total weight of animals in the monitoring area of ​​the corresponding farm are larger, and the environmental quality concern is greater, that is, the monitoring area of ​​the corresponding farm is highly likely to have local accumulation of harmful gases, which will seriously threaten the health of the animals; then, greater weight needs to be given to the environmental quality concern of these monitoring areas. The DBSCAN clustering algorithm is an existing technology, and will not be described in detail here.

[0087] The first In the cluster, the th The product of the number of animals and their total weight in each monitoring area is denoted as the i-th. Animal impact factors in the monitoring area; the first Animal impact factors in the first monitoring area and the first The ratio of the area of ​​each monitoring area is denoted as the th monitoring area. The regional impact factor of the monitoring area; will the first The regional impact factor of each monitoring area and the current time of the [missing information] The product of the environmental quality concerns of each monitoring area is denoted as the product of the environmental quality concerns at the current time. Environmental quality focus weight for each monitoring area;

[0088] The first The normalized value of the sum of the environmental quality concern weights of all monitored areas in each cluster at the current time is used as the value of the i-th cluster at the current time. The degree of local accumulation of harmful gases in each cluster;

[0089] The average degree of local accumulation of harmful gases in all clusters at the current moment is taken as the overall environmental quality concern at the current moment.

[0090] The specific formula is as follows:

[0091]

[0092] In the formula, Indicates the next time step. The degree of local accumulation of harmful gases in each cluster; Indicates the first The number of all monitored areas in each cluster; Indicates the first In the cluster, the th The area of ​​each monitoring zone; and They represent the first In the cluster, the th The number and total weight of animals in each monitoring area; Indicates the next time step. In the cluster, the th Environmental quality concerns in each monitoring area; This represents the linear normalization function.

[0093] Preferably, in one embodiment of the present invention, the specific method for obtaining the sampling frequency adjustment coefficient for the next cycle in the farm based on the comprehensive environmental quality concern is as follows:

[0094] Using the current level of public concern about the overall environmental quality as a weight, the ammonia concentration data at the current moment is input into the weighted prediction algorithm to obtain the ammonia concentration data sequence for the next cycle in the farm.

[0095] Preset a normal ammonia concentration threshold In this embodiment, This example is used for illustration; no specific limitations are set in this embodiment. It depends on the specific implementation situation;

[0096] The mean of all ammonia concentration data in the next cycle of the ammonia concentration data series in the farm is compared with the normal ammonia concentration threshold. The ratio between them is used as the sampling frequency adjustment coefficient for the next cycle in the farm.

[0097] It should be noted that the weighted prediction algorithm is existing technology and will not be described in detail here. By taking comprehensive environmental quality concern and ammonia concentration data as input and combining them with the weighted prediction algorithm, the ammonia concentration in the farm for the next cycle can be predicted more accurately. This accurate prediction capability can provide farm managers with more timely and accurate early warning information, help control the concentration of harmful gases, and ensure the safety of the farming environment.

[0098] At this point, the sampling frequency adjustment coefficient for the next cycle in the breeding farm is obtained.

[0099] Step S004: Adaptively adjust the collection frequency of environmental data in the farm for the next cycle according to the collection frequency adjustment coefficient.

[0100] Preferably, in one embodiment of the present invention, the specific method for adaptively adjusting the collection frequency of environmental data in the farm for the next cycle according to the collection frequency adjustment coefficient is as follows:

[0101] The product of the current sampling frequency and the sampling frequency adjustment coefficient for the next cycle in the farm is rounded up and used as the sampling frequency for the next cycle in the farm.

[0102] It should be noted that by adaptively adjusting the environmental data collection frequency, the collection frequency can be increased at critical moments (such as when ammonia concentration fluctuates significantly) to capture more data on environmental changes. Conversely, the collection frequency can be reduced when the environment is stable, saving resources and avoiding data redundancy.

[0103] Please see Figure 2 It shows a flowchart of the characteristic relationships of a method for collecting data on livestock farming environment;

[0104] This concludes the embodiment.

[0105] Another embodiment of the present invention provides a livestock breeding environment data acquisition system, the system including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the above method steps S001 to S004.

[0106] Another embodiment of the present invention provides a livestock farming environment data acquisition medium, the medium comprising:

[0107] The system includes a data acquisition module, a data acquisition frequency adjustment coefficient acquisition module, and a data acquisition frequency adjustment module. The data acquisition module is used to acquire periodic multidimensional environmental data sequences of several monitoring areas within the farm, as well as the number and total weight of animals. The data acquisition frequency adjustment coefficient acquisition module calls a computer program to implement steps S001 to S003 of the above method to obtain the data acquisition frequency adjustment coefficient for the next period within the farm. The data acquisition frequency adjustment module adaptively adjusts the data acquisition frequency of the environmental data for the next period within the farm based on the data acquisition frequency adjustment coefficient.

[0108] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for collecting livestock farming environment data, characterized in that, The method includes the following steps: Acquire periodic multidimensional environmental data sequences for several monitoring areas within the farm, as well as the number and total weight of animals; the multidimensional environmental data includes: ammonia concentration, carbon dioxide concentration, temperature data, humidity data, and light intensity; By analyzing the changes in ammonia and carbon dioxide concentrations in the periodic multidimensional environmental data series of the monitoring area, the degree of fecal accumulation in the monitoring area at the current moment is obtained; by analyzing the influence of other dimensions of environmental data on the changes in ammonia and carbon dioxide concentrations, the degree of fecal fermentation impact in the monitoring area at the current moment is obtained; based on the degree of fecal fermentation impact and the degree of fecal accumulation, the level of concern regarding the impact of feces in the monitoring area at the current moment is obtained. Based on the differences in the level of concern about the impact of feces between the monitoring area and surrounding monitoring areas, the environmental quality concern level of each monitoring area at the current moment is obtained; by analyzing the environmental quality concern level, animal number and total weight of different monitoring areas, a concern weight is assigned to different monitoring areas to obtain the comprehensive environmental quality concern level at the current moment; based on the comprehensive environmental quality concern level, the sampling frequency adjustment coefficient for the next cycle in the farm is obtained; The frequency of environmental data collection in the farm for the next cycle is adaptively adjusted based on the collection frequency adjustment coefficient.

2. The method for collecting livestock farming environment data according to claim 1, characterized in that, The method for obtaining the degree of fecal accumulation in the monitoring area at the current moment by analyzing the changes in ammonia and carbon dioxide concentrations in the periodic multidimensional environmental data sequence of the monitoring area includes the following specific methods: In the periodic multidimensional environmental data sequence of the monitoring area, all sampling times before the current time are recorded as historical times; The least squares method was used to fit curves of ammonia and carbon dioxide concentration data of the monitoring area at all historical times, so as to obtain the ammonia and carbon dioxide change curves of the monitoring area at the current time. The ratio between the ammonia concentration data of the monitoring area at the current moment and the maximum ammonia concentration data value in the ammonia change curve of the monitoring area at the current moment is recorded as the first fecal maximum accumulation factor; the ratio between the carbon dioxide concentration data of the monitoring area at the current moment and the maximum carbon dioxide concentration data value in the carbon dioxide change curve of the monitoring area at the current moment is recorded as the second fecal maximum accumulation factor; the average of the first fecal maximum accumulation factor and the second fecal maximum accumulation factor is taken as the fecal accumulation degree of the monitoring area at the current moment.

3. The method for collecting livestock farming environment data according to claim 2, characterized in that, The method for analyzing the impact of changes in ammonia and carbon dioxide concentrations on environmental data from other dimensions to obtain the degree of influence of fecal fermentation in the monitored area at the current moment includes the following specific methods: Temperature data, humidity data, and light intensity are all recorded as influencing data; The mean of the standard deviations of ammonia and carbon dioxide concentration data for the monitoring area at all historical moments is recorded as the gas fluctuation amplitude of the monitoring area at the current moment; the... The gas fluctuation amplitude of the monitored area at the first historical moment and the first The absolute value of the difference between the gas fluctuation amplitudes of the monitored area at each historical moment is denoted as the nth. The gas fluctuation changes in the monitoring area at each historical moment; the sequence of gas fluctuation changes in the monitoring area at all historical moments is denoted as the gas fluctuation change sequence of the monitoring area at the current moment. The monitoring area at all historical moments The standard deviation of the impact data of each dimension is denoted as the first standard deviation of the monitored area at the current time. The impact of each dimension on the fluctuation range of the data; The monitoring area at the first historical moment The fluctuation range of the impact data of the first dimension and the second dimension The monitoring area at the first historical moment The absolute value of the difference between the fluctuation amplitudes of the data in each dimension is denoted as the _th_. The monitoring area at the first historical moment The fluctuation and change of data in each dimension; the first dimension of the monitoring area at all historical moments. The sequence of fluctuations in the data across various dimensions is denoted as the first (i) of the monitored area at the current moment. The sequence of fluctuations in data affecting various dimensions; The mean of the Pearson correlation coefficients between the gas fluctuation change sequence of the monitoring area at the current moment and the fluctuation change sequences of all dimensions of influence data in the monitoring area at the current moment is taken as the degree of influence of fecal fermentation in the monitoring area at the current moment.

4. The method for collecting livestock breeding environment data according to claim 1, characterized in that, The method for obtaining the level of concern regarding the impact of fecal fermentation and the degree of fecal accumulation in the monitored area at the current moment includes the following specific methods: The normalized value of the product of the degree of fecal fermentation impact in the monitored area at the current moment and the cumulative degree of fecal matter in the monitored area at the current moment is taken as the fecal impact concern level in the monitored area at the current moment.

5. The method for collecting livestock farming environment data according to claim 1, characterized in that, The method for obtaining the environmental quality concern level of each monitoring area at the current moment based on the difference in concern level regarding the impact of feces between the monitoring area and surrounding monitoring areas includes the following specific methods: Preset a neighborhood parameter , obtain the The distance between the center of each monitoring area and the center of all other monitoring areas; the nearest front Each of the monitoring areas is considered as the first monitoring area. Adjacent monitoring areas of each monitoring area; According to the The monitoring area and the first The differences in distance and concern regarding the impact of feces between adjacent monitoring areas were obtained to determine the first... The monitoring area and the first The degree of gas diffusion impact between adjacent monitoring areas; The current moment is the next The sum of the gas diffusion influence between the current monitoring area and all adjacent monitoring areas is denoted as the first sum; the first sum is then compared with the sum of the gas diffusion influence between the current monitoring area and all adjacent monitoring areas. The normalized value of the product of the public's concern about the impact of feces on each monitoring area is used as the value of the first monitoring area at the current moment. Environmental quality concerns in each monitoring area.

6. The method for collecting livestock farming environment data according to claim 5, characterized in that, According to the first The monitoring area and the first The differences in distance and concern regarding the impact of feces between adjacent monitoring areas were obtained to determine the first... The monitoring area and the first The degree of gas diffusion influence between adjacent monitoring areas includes the following specific methods: The current moment is the next The level of concern regarding the impact of feces in the monitoring areas is comparable to that of the first monitoring area. The first monitoring area The absolute value of the difference between the level of concern regarding the impact of feces on adjacent monitoring areas is denoted as the first absolute value of the difference; the first absolute value of the difference is compared with the first absolute value of the difference. The monitoring area and the first The ratio of the distances between the centers of adjacent monitoring areas is used as the ratio of the distances between the centers of adjacent monitoring areas at the current time. The monitoring area and the first The degree of gas diffusion impact between adjacent monitoring areas.

7. The method for collecting livestock breeding environment data according to claim 1, characterized in that, The method for assigning different attention weights to different monitoring areas by analyzing environmental quality concern, animal numbers, and total weight in different monitoring areas to obtain the comprehensive environmental quality concern at the current moment includes the following specific methods: The current location of the center of each monitoring area, the environmental quality concern, the number of animals and the total weight are used as the feature vector of each monitoring area. Based on the Euclidean distance between the feature vectors of the monitoring areas, the DBSCAN clustering algorithm is used to cluster all monitoring areas in the farm to obtain several clusters. The first In the cluster, the th The product of the number of animals and their total weight in each monitoring area is denoted as the i-th. Animal impact factors in the monitoring area; the first Animal impact factors in the first monitoring area and the first The ratio of the area of ​​each monitoring area is denoted as the ratio of the area of ​​the first monitoring area to the area of ​​the second monitoring area. The regional impact factor of the monitoring area; will the first The regional impact factor of each monitoring area and the current time of the [missing information] The product of the environmental quality concerns of each monitoring area is denoted as the product of the environmental quality concerns at the current time. Environmental quality focus weight for each monitoring area; The first The normalized value of the sum of the environmental quality concern weights of all monitored areas in each cluster at the current time is used as the value of the i-th cluster at the current time. The degree of local accumulation of harmful gases in each cluster; The average degree of local accumulation of harmful gases in all clusters at the current moment is taken as the overall environmental quality concern at the current moment.

8. The method for collecting livestock farming environment data according to claim 1, characterized in that, The specific method for obtaining the sampling frequency adjustment coefficient for the next cycle within the farm based on comprehensive environmental quality concern is as follows: Using the current level of public concern about the overall environmental quality as a weight, the ammonia concentration data at the current moment is input into the weighted prediction algorithm to obtain the ammonia concentration data sequence for the next cycle in the farm. Preset a normal ammonia concentration threshold The mean of all ammonia concentration data in the next cycle of the ammonia concentration data series in the farm is compared with the normal ammonia concentration threshold. The ratio between them is used as the sampling frequency adjustment coefficient for the next cycle in the farm.

9. A livestock farming environment data acquisition system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the livestock breeding environment data acquisition method as described in any one of claims 1-8.

10. A livestock farming environment data acquisition medium, characterized in that, The medium includes: The system includes a data acquisition module, a data acquisition frequency adjustment coefficient acquisition module, and a data acquisition frequency adjustment module. The data acquisition module is used to acquire periodic multidimensional environmental data sequences of several monitoring areas within the farm, as well as the number and total weight of animals. The data acquisition frequency adjustment coefficient acquisition module implements the steps of the livestock farming environmental data acquisition method as described in any one of claims 1-8 by calling a computer program to obtain the data acquisition frequency adjustment coefficient for the next period within the farm. The data acquisition frequency adjustment module adaptively adjusts the data acquisition frequency of the environmental data for the next period within the farm based on the data acquisition frequency adjustment coefficient.

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