An environmental pollution information monitoring method applicable to livestock farming

Abstract

The present invention relates to the technical field of environmental information monitoring, and particularly relates to an environmental pollution information monitoring method applicable to livestock farming, including: obtaining the activity information of livestock to be monitored, and dividing the breeding area into at least two sub-areas; correspondingly obtaining position parameters according to the sub-area information, and obtaining influence attribute parameters according to the position parameters and the activity information; obtaining the confidence level of the excretion behavior time according to the activity information, and obtaining the environmental impact degree value of livestock farming on each sub-area according to the confidence level, the influence attribute parameters, and the activity information; determining the pollution impact degree value of the livestock farming on the environment according to each environmental impact degree value and the nitrogen and phosphorus contents of the sampling points in each sub-area. By adopting the present invention, the impact of livestock farming on the local environment can be accurately monitored and evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental information monitoring, and particularly relates to a method for monitoring environmental pollution information applicable to livestock breeding. Background Art

[0002] With the continuous expansion of the scale of the breeding industry and the transformation and upgrading of the breeding mode, the traditional breeding mode is facing multiple challenges, including low production efficiency, aggravated environmental pollution, lax product quality control, and ineffective epidemic prevention and control. In today's era of advocating green ecology and environment-friendly industries, it is particularly crucial to strictly control the environmental pollution caused by breeding. To address these challenges, intelligent breeding, refined management, and environment-friendly livestock industries are gradually becoming the core directions of the development of the livestock industry.

[0003] In the livestock industry, the negative impact of livestock manure on the environment is particularly significant. If the manure discharge exceeds the environmental carrying capacity, elements such as nitrogen and phosphorus in it may cause environmental problems such as water eutrophication and soil salinization. Therefore, it is crucial to accurately detect the nitrogen and phosphorus content in manure. However, due to the scattered discharge of manure, it is difficult for sampling points to comprehensively represent the nitrogen and phosphorus content of the entire breeding area, thereby affecting the accuracy of environmental impact assessment.

[0004] When detecting the nitrogen and phosphorus content of manure in the breeding area in the prior art, the grid sampling method is generally adopted, that is, the breeding area is evenly divided into several sampling areas, and sampling is carried out in each sampling area. According to the collected samples of each sampling area, after testing, cumulative summation is performed to obtain the nitrogen and phosphorus content of the livestock manure in the breeding area. However, through sampling and detection in the evenly divided sampling areas, due to the unevenness of livestock activities, there are differences in the nitrogen and phosphorus content of each sampling area, and the nitrogen and phosphorus content of the livestock manure in some sampling areas cannot accurately reflect the actual impact of livestock breeding on the local environment, resulting in low accuracy of detection and evaluation. Summary of the Invention

[0005] In order to solve the technical problem of inaccurate monitoring and evaluation of the impact of livestock breeding on the local environment, the purpose of the present invention is to provide a method for monitoring environmental pollution information applicable to livestock breeding, and the specific technical solutions adopted are as follows:

[0006] Obtain the activity information of the livestock to be monitored, and divide the breeding area into at least two sub-areas;

[0007] Obtain the position parameters corresponding to the sub-area information, and obtain the influence attribute parameters according to the position parameters and the activity information;

[0008] Obtain the confidence level of the excretion behavior time according to the activity information, and obtain the environmental impact degree value of livestock breeding on each sub-area according to the confidence level, the influence attribute parameters, and the activity information;

[0009] Determine the pollution impact degree value of the livestock farming on the environment according to each of the environmental impact degree values and the nitrogen and phosphorus contents of the sampling points in each sub-region.

[0010] Further, the corresponding acquisition of the position parameter according to the sub-region information includes:

[0011] Obtain the total area of the breeding area, the area of the low elevation area in the i-th sub-region and the standard deviation of the elevation change, and the cumulative difference of the elevation change between the i-th sub-region and the adjacent sub-region, where the area of the low elevation area represents the area in the i-th sub-region where the elevation is lower than the average elevation of the breeding area, the total area is equal to the sum of the areas of each sub-region, and the value range of i is from 1 to the number of sub-regions;

[0012] Divide the area by the total area first, and then multiply by the cumulative difference to obtain the first multiplier;

[0013] After adding a first preset value to the standard deviation, take the reciprocal to obtain the second multiplier;

[0014] Multiply the first multiplier and the second multiplier as the input value of the Sigmoid function, and use the output value of the Sigmoid function as the position parameter corresponding to the i-th sub-region;

[0015] Repeat the process of obtaining the position parameter to obtain the position parameters corresponding to each sub-region.

[0016] Further, obtaining the influence attribute parameter according to the position parameter and the activity information includes:

[0017] Obtain the residence time, total activity path length, repeated activity path length and number of activity turning points of the livestock to be monitored in the i-th sub-region in the activity information, where the value range of i is from 1 to the number of sub-regions;

[0018] Multiply the position parameter, the residence time, the repeated activity path length and the number of activity turning points in sequence, and then divide by the total activity path length to obtain the influence attribute parameter corresponding to the i-th sub-region;

[0019] Repeat the process of obtaining the influence attribute parameter to obtain the influence attribute parameters corresponding to each sub-region.

[0020] Further, obtaining the confidence degree of the excretion behavior time according to the activity information includes:

[0021] Obtain the residence duration of each time on the activity path of the livestock to be monitored in the i-th sub-region in the activity information, and cluster the residence durations as data points to obtain a preset number of clusters, where the value range of i is from 1 to the number of sub-regions;

[0022] The cluster corresponding to the one with the smallest average value of the data points is the excretion behavior time cluster;

[0023] Obtain the confidence level that each residence duration is the excretion behavior time according to the activity information and the excretion behavior time cluster.

[0024] Furthermore, obtaining the confidence level that each residence duration is the excretion behavior time according to the activity information and the excretion behavior time cluster includes:

[0025] Obtain the number of the residence durations that are the same as the v-th residence duration in the excretion behavior time cluster as the first quantity, and obtain the total number of the residence durations in the excretion behavior time cluster, where the value range of v is from 1 to the number of the residence durations in the excretion behavior time cluster;

[0026] Obtain the first speed of the livestock to be monitored before the v-th residence duration and the second speed of the livestock to be monitored after the v-th residence duration in the activity information;

[0027] After subtracting the first speed from the second speed, divide the result by the first speed to obtain the speed change value;

[0028] Take the opposite of the absolute value of the speed change value as the input value of the exponential function;

[0029] After dividing the first quantity by the total quantity, multiply the result by the output value of the exponential function to be used as the input value of the Sigmoid function, and the output value of the Sigmoid function is the confidence level that the v-th residence duration is the excretion behavior time;

[0030] Repeat the process of obtaining the confidence level to obtain the confidence level that each residence duration is the excretion behavior time.

[0031] Furthermore, obtaining the environmental impact degree value of livestock farming on each sub-region according to the confidence level, the influence attribute parameter, and the activity information includes:

[0032] Obtain the v-th residence duration in the excretion behavior time cluster and the v-th confidence level that the v-th residence duration is the excretion behavior time, where the value range of v is from 1 to the number of residence durations in the excretion behavior time cluster;

[0033] After multiplying the v-th residence duration by the v-th confidence level, divide it by the total stationary time of the livestock to be monitored in the i-th sub-region to obtain the third multiplier corresponding to the v-th residence duration;

[0034] Repeat the process of obtaining the third multiplier to obtain the third multipliers corresponding to each residence duration in the excretion behavior time cluster, and add the third multipliers in sequence to obtain the total multiplier value;

[0035] Multiply the total multiplier value, the influence attribute parameter, and the foraging behavior description value in sequence as the input value of the Sigmoid function. The output value of the Sigmoid function is the environmental impact degree value of the livestock farming on the i-th sub-region, where the foraging behavior description value is the product of the number of activity inflection points in the activity information and the length of the repeated activity path in the activity information;

[0036] Repeat the process of obtaining the environmental impact degree value to obtain the environmental impact degree values of the livestock farming on each sub-region.

[0037] Further, clustering the residence durations as data points to obtain a preset number of clusters includes:

[0038] Use the K-means algorithm to cluster the data points to obtain a preset number of clusters. The residence durations are used as the data points, and the preset number includes two.

[0039] Further, determining the pollution impact degree value of the livestock farming on the environment according to each environmental impact degree value and the nitrogen and phosphorus contents of the sampling points in each sub-region includes:

[0040] Obtain the product of the environmental impact degree value of the i-th sub-region and the nitrogen and phosphorus contents of the sampling points in the i-th sub-region to obtain the pollution impact degree value of the i-th sub-region on the environment, where the value range of i is from 1 to the number of sub-regions;

[0041] Repeat the process of obtaining the pollution impact degree value to obtain the pollution impact degree values of each sub-region on the environment;

[0042] Add the pollution impact degree values in sequence to obtain the pollution impact degree value of the livestock farming on the environment.

[0043] Further, the division of the breeding area into at least two sub-areas includes:

[0044] Obtain a satellite image of the breeding area, and divide the satellite image into at least two sub-areas by using the grid sampling method.

[0045] Further, the livestock to be monitored includes the leading sheep.

[0046] The present invention has the following beneficial effects:

[0047] First, obtain the activity information of the livestock to be monitored, and divide the breeding area into at least two sub-areas. This is the data basis for subsequent analysis. Second, obtain the position parameters corresponding to the sub-area information, and obtain the influence attribute parameters according to the position parameters and the activity information. The position parameters are used as the weights for obtaining the influence attribute parameters, and are positively correlated with the influence attribute parameters. The larger the influence attribute parameter, the greater the influence degree of the livestock on the area. Third, obtain the confidence of the excretion behavior time according to the activity information, and obtain the environmental impact degree value of the livestock breeding on each sub-area according to the confidence, the influence attribute parameter, and the activity information. Here, the environmental impact degree value of the livestock breeding on each sub-area is obtained by combining the confidence, the influence attribute parameter, and the activity information, which are three aspects related to the current environmental impact of the livestock breeding. Finally, determine the pollution impact degree value of the livestock breeding on the environment according to the environmental impact degree values and the nitrogen and phosphorus contents of the sampling points in each sub-area. By representing the environmental impact of the livestock breeding on different sub-areas with different weights, that is, the environmental impact degree values, assigned to different sub-areas in the breeding area, the environmental impact of the livestock breeding on the breeding area can be evaluated more accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0049] Figure 1 It is a flowchart of a method for monitoring environmental pollution information applicable to livestock breeding provided by the first embodiment of the present invention;

[0050] Figure 2 It is a flowchart of the acquisition process of the position parameters provided by the second embodiment of the present invention;

[0051] Figure 3 The flowchart of the acquisition process of the influence attribute parameter provided by the third embodiment of the present invention;

[0052] Figure 4 The flowchart of the acquisition process of the confidence level provided by the fourth embodiment of the present invention;

[0053] Figure 5 Another flowchart of the acquisition process of the confidence level provided by the fifth embodiment of the present invention;

[0054] Figure 6 The flowchart of the acquisition process of the environmental impact degree value provided by the sixth embodiment of the present invention;

[0055] Figure 7 The flowchart of the acquisition process of the pollution impact degree value provided by the seventh embodiment of the present invention. Detailed implementation manners

[0056] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following combines the drawings and preferred embodiments to detail the specific implementation manners, structures, features and effects of an environmental pollution information monitoring method applicable to livestock breeding proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0058] The following specifically describes the specific solution of an environmental pollution information monitoring method applicable to livestock breeding provided by the present invention with reference to the drawings.

[0059] Please refer to Figure 1 , which shows the flowchart of the environmental pollution information monitoring method applicable to livestock breeding provided by the first embodiment of the present invention. The method includes:

[0060] S101. Obtain the activity information of the livestock to be monitored, and divide the breeding area into at least two sub-areas.

[0061] Optionally, when this embodiment takes the flock as the research object, due to the aggregation effect of the leading sheep in the flock, at this time, the livestock to be monitored can be the leading sheep.

[0062] The activity information may include: the activity trajectory of the livestock to be monitored in the breeding area, the residence time at different locations, the movement speed, etc. By using the positioning device worn on the livestock to be monitored, the activity information in the breeding area is collected in real time and synchronized, and these activity information are immediately uploaded to the environmental monitoring information data center through the wireless network.

[0063] Specifically, the dividing the breeding area into at least two sub-areas includes:

[0064] Obtain the satellite image of the breeding area, and divide the satellite image into at least two sub-areas by using the grid sampling method.

[0065] That is to say, according to the relevant regulations on the grid division of ecological environment monitoring sampling points, several areas (the area is smaller than the breeding area and is a sub-area of the breeding area) are evenly divided in the breeding area by using the grid sampling method through the satellite image of the breeding area.

[0066] S102. Obtain the position parameters corresponding to the sub-area information, and obtain the influence attribute parameters according to the position parameters and the activity information.

[0067] The sub-area information includes: the area of the low elevation area in the i-th sub-area and the standard deviation of the elevation change, and the cumulative difference of the elevation change between the i-th sub-area and the adjacent sub-areas. Among them, the area of the low elevation area represents the area where the elevation in the i-th sub-area is lower than the average elevation of the breeding area. The total area is equal to the sum of the areas of each sub-area, and the value range of i is from 1 to the number of sub-areas.

[0068] The sum of the areas of each sub-area is the total area of the breeding area.

[0069] When the proportion of the low elevation area in the i-th sub-area in the breeding area is larger, it means that the altitude of the location where the i-th sub-area is located is lower. The lower the altitude, that is, the lower the terrain. In the area with lower terrain, the growth of water plants is better, and livestock are more willing to forage in this area.

[0070] When the elevation change of the i-th sub-area is small, that is, when the slope change of the i-th sub-area is small, the terrain of the i-th sub-area is flatter. The flat terrain will make it easier for livestock to forage. When livestock forage in another sub-area with a large elevation change, it will consume more energy of livestock and increase the difficulty of livestock foraging. Therefore, livestock are more willing to forage in the i-th sub-area, that is, the sub-area with a small elevation change. As a result, the influence degree of livestock on the i-th sub-area is greater, that is, the position parameter of the i-th sub-area is larger.

[0071] The process of obtaining the position parameter will be described in detail in the second embodiment and will not be elaborated here.

[0072] The more activity trajectories of livestock in a certain area and the longer the staying time, it indicates that the impact of livestock activities on this area is greater. That is to say, the environmental destructiveness caused to this area is greater. Then, when conducting an environmental impact analysis of livestock farming, the representativeness of this area is greater. That is to say, this area can better reflect the impact of livestock farming on the environment.

[0073] When the repeatability of the path trajectory of livestock moving in the i-th sub-area is higher, it indicates that the possibility of livestock foraging in the i-th sub-area is higher. Because when livestock are foraging and grazing, their activity paths will be repetitive, without a clear direction and with a relatively long staying time. While when livestock are running, their activity paths often have a clear direction, a single trajectory, a relatively fast speed, a short staying time, and low repeatability.

[0074] The process of obtaining the impact attribute parameter will be described in detail in the third embodiment and will not be elaborated here.

[0075] S103. Obtain the confidence level of the excretion behavior time according to the activity information, and obtain the environmental impact degree value of livestock farming on each sub-area according to the confidence level, the impact attribute parameter, and the activity information.

[0076] The determination of the environmental impact degree value is affected by the combined action of multiple factors:

[0077] First, based on the activity path of livestock, deeply analyze the staying duration of livestock when moving in the i-th sub-area. Considering that the excretion behavior of livestock is often static, therefore, the longer the staying time of livestock in the i-th sub-area, it means that the foraging activity is more frequent, and the possibility of excretion also increases accordingly. This frequent excretion activity significantly improves the degree of impact of this area on livestock farming and enhances its representativeness as an environmental impact assessment indicator.

[0078] However, it should be noted that the staying duration of livestock in the i-th sub-area is not directly equal to the frequency of excretion behavior. During the staying period, livestock may be in the excretion state or may be resting. Since the normal excretion behavior of livestock takes a relatively fixed and short time, while the rest behavior may last for a relatively long time and the duration is uncertain, so within a certain time range, the excretion frequency of livestock is often more than the rest frequency. But the impact of a single excretion on foraging is much smaller than that of rest, and after excretion, the sheep will quickly resume foraging activities without changing the original trajectory. In contrast, during rest, the body posture changes of livestock (such as semi-lateral lying) and the relatively long rest time may lead to adjustments in the activity trajectory, such as running for digestion, moving the torso, etc.

[0079] Based on the above analysis, combined with the activity paths of livestock, their residence times, and the characteristics of excretion and rest behaviors, the environmental impact degree value of livestock farming on the i-th sub-region was comprehensively evaluated. This evaluation not only considered the activity frequency and excretion behavior of livestock but also deeply analyzed the impact of rest behavior on the activity trajectories, thus more accurately reflecting the actual impact of livestock farming on the environment.

[0080] The process of obtaining the confidence level will be described in detail in the fourth and fifth embodiments and will not be elaborated here.

[0081] The process of obtaining the environmental impact degree value will be described in detail in the sixth embodiment and will not be elaborated here.

[0082] S104. Determine the pollution impact degree value of the livestock farming on the environment according to each of the environmental impact degree values and the nitrogen and phosphorus contents at the sampling points in each sub-region.

[0083] Determine the pollution impact degree value of the livestock farming on the environment according to the environmental impact degree value of the sub-region and the nitrogen and phosphorus contents at the sampling points.

[0084] The process of obtaining the pollution impact degree value will be described in detail in the seventh embodiment and will not be elaborated here.

[0085] Figure 2 This is a flowchart of the process for obtaining the position parameters provided in the second embodiment of the present invention. The corresponding obtaining of the position parameters according to the sub-region information includes:

[0086] S201. Obtain the total area of the breeding area, the area of the low-elevation area in the i-th sub-region, the standard deviation of the elevation change, and the cumulative difference in elevation change between the i-th sub-region and the adjacent sub-regions. The area of the low-elevation area represents the area in the i-th sub-region where the elevation is lower than the average elevation of the breeding area. The total area is equal to the sum of the areas of each sub-region, where the value range of i is from 1 to the number of sub-regions.

[0087] Elevation refers to the vertical distance from a certain point on the ground to a certain horizontal plane. The area of the low-elevation area in the i-th sub-region represents the elevation in the i-th sub-region lower than the average elevation of the breeding area of the area.

[0088] S202. Divide the area by the total area first and then multiply by the cumulative difference to obtain the first multiplier.

[0089] The first multiplier can be expressed as: where the represents the area of the region, S represents the total area, and A represents the cumulative difference.

[0090] S203. After adding a first preset value to the standard deviation, take the reciprocal to obtain a second multiplier.

[0091] The second multiplier can be expressed as: , where represents the standard deviation, k represents the first preset value, and k can be set independently, preferably 1.

[0092] S204. Multiply the first multiplier and the second multiplier and use the result as the input value of the Sigmoid function, and use the output value of the Sigmoid function as the position parameter corresponding to the i-th sub-region.

[0093] The position parameter can be expressed as:

[0094] ;

[0095] where represents the position parameter corresponding to the i-th sub-region.

[0096] Since the Sigmoid function is monotonically increasing, the larger , the smaller , the larger A, then the larger .

[0097] S205. Repeat the process of obtaining the position parameter to obtain the position parameters corresponding to each sub-region.

[0098] Figure 3 is the flowchart of the process for obtaining the influence attribute parameter provided by the third embodiment of the present invention. Obtaining the influence attribute parameter according to the position parameter and the activity information includes:

[0099] S301. Obtain the residence time, total activity path length, repeated activity path length, and activity turning point number of the livestock to be monitored in the i-th sub-region in the activity information, where the value range of i is from 1 to the number of sub-regions.

[0100] S302. Multiply the position parameter, the residence time, the repeated activity path length, and the activity turning point number in sequence, and then divide by the total activity path length to obtain the influence attribute parameter corresponding to the i-th sub-region.

[0101] The influence attribute parameter can be expressed as:

[0102] ;

[0103] Among them, the represents the position parameter, and the represents the residence time, and the represents the length of the repeated activity path, and the represents the number of turning points of the activity, and the represents the total length of the activity path. The function is a prior art and will not be elaborated here.

[0104] When the position attribute of the i-th sub-region is better, that is, the position parameter is larger, which means it can attract livestock to forage more. Further, when the livestock stay in the i-th sub-region for a longer time, the degree of influence on the i-th sub-region will necessarily be greater. Taking as the weight, it represents the confidence level of the influence behavior of the livestock in the i-th sub-region; represents the description of the foraging activity of the livestock. The more repeated paths the livestock walks and the more turning points there are in the path (compared with behaviors such as running, the foraging behavior has no clear goal and the degree of path messiness is relatively large, that is, there are more turning points in the path), which means the greater the possibility that it is a foraging activity, represents the proportion of the foraging behavior path. The larger the proportion of the foraging behavior in the i-th sub-region, the greater the degree of influence of the livestock's behavior on the environment. That is to say, the larger the influence attribute parameter of the livestock in the i-th sub-region, that is, is larger.

[0105] S303. Repeat the process of obtaining the influence attribute parameter to obtain the influence attribute parameters corresponding to each sub-region.

[0106] Figure 4 This is the flowchart of the process for obtaining the confidence level provided by the fourth embodiment of the present invention. Obtaining the confidence level of the excretion behavior time according to the activity information includes:

[0107] S401. Obtain the residence duration of each time on the activity path of the livestock to be monitored in the i-th sub-region in the activity information, and use the residence duration as data points for clustering to obtain a preset number of clusters, where the value range of i is from 1 to the number of sub-regions.

[0108] Because the excretion behavior of livestock takes a relatively stable time and the number of excretion behaviors is relatively large, the clustering can be performed according to the residence duration of each time on the activity path of the livestock in the i-th sub-region.

[0109] Specifically, using the residence duration as data points for clustering to obtain a preset number of clusters includes:

[0110] The K-means algorithm is used to cluster data points to obtain a preset number of clusters, where the residence duration is used as the data point, and the preset number includes two.

[0111] S402. The cluster corresponding to the data point with the smallest average value is the excretion behavior time cluster.

[0112] S403. According to the activity information and the excretion behavior time cluster, obtain the confidence level that each residence duration is the excretion behavior time.

[0113] Figure 5 Another flowchart of the confidence level acquisition process provided by the fifth embodiment of the present invention. Obtaining the confidence level that each residence duration is the excretion behavior time according to the activity information and the excretion behavior time cluster includes:

[0114] S501. Obtain the number of residence durations that are the same as the v-th residence duration in the excretion behavior time cluster as the first quantity, and obtain the total number of residence durations in the excretion behavior time cluster, where the value range of v is from 1 to the number of residence durations in the excretion behavior time cluster.

[0115] S502. Obtain the first speed of the livestock to be monitored before the v-th residence duration and the second speed of the livestock to be monitored after the v-th residence duration in the activity information.

[0116] The first speed can be the average speed within a preset first time before the v-th residence duration. The second speed can be the average speed within a preset second time after the v-th residence duration. The preset first time and the preset second time can be set reasonably by oneself and are not limited here.

[0117] S503. After subtracting the first speed from the second speed, divide by the first speed to obtain the speed change value;

[0118] The speed change value can be expressed as: , the represents the second speed, and the represents the first speed.

[0119] S504. Use the opposite of the absolute value of the speed change value as the input value of the exponential function.

[0120] The input value of the exponential function can be expressed as:

[0121] .

[0122] After dividing the first quantity by the total quantity, multiply the result by the output value of the exponential function to obtain the input value of the Sigmoid function. The output value of the Sigmoid function is the confidence level that the v-th residence duration is the excretion behavior time.

[0123] The confidence level can be expressed as:

[0124] ;

[0125] where represents the confidence level, represents the first quantity, represents the total quantity, and exp is the exponential function with the natural constant as the base. The function is a prior art and will not be elaborated here.

[0126] When is smaller, it indicates that the speed change of the livestock before and after the v-th data point, i.e., the v-th residence duration, is smaller, which means that the possibility that the v-th residence duration is the excretion behavior time of the livestock is greater. When the is larger, it means that the proportion of the excretion behavior time of the livestock is larger, and the v-th residence duration is more likely to be the excretion behavior time. The is larger, and the credibility that the v-th residence duration is the excretion behavior time is higher.

[0127] S506. Repeat the process of obtaining the confidence level to obtain the confidence level that each residence duration is the excretion behavior time.

[0128] Figure 6 This is the flowchart of the environmental impact degree value provided by the sixth embodiment of the present invention. Obtaining the environmental impact degree value of livestock farming on each sub-region according to the confidence level, the impact attribute parameter, and the activity information includes:

[0129] S601. Obtain the v-th residence duration in the excretion behavior time cluster and the v-th confidence level that the v-th residence duration is the excretion behavior time, where the value range of v is from 1 to the number of residence durations in the excretion behavior time cluster.

[0130] S602. After multiplying the v-th residence duration by the v-th confidence level, divide the result by the total static time of the livestock to be monitored in the i-th sub-region to obtain the third multiplier corresponding to the v-th residence duration.

[0131] The third multiplier can be expressed as: , where represents the v-th stay duration, and represents the v-th confidence level, and represents the total stationary time of the livestock to be monitored within the i-th sub-region.

[0132] S603. Repeat the process of obtaining the third multiplier to obtain the third multipliers corresponding to the stay durations in the excretion behavior time clusters, and sum up the third multipliers in sequence to obtain the total multiplier value.

[0133] The total multiplier value can be expressed as: , where V is the number of the third multipliers.

[0134] S604. Multiply the total multiplier value, the impact attribute parameter, and the foraging behavior description value in sequence and use the result as the input value of the Sigmoid function. The output value of the Sigmoid function is the environmental impact degree value of the livestock farming on the i-th sub-region. Among them, the foraging behavior description value is the product of the number of activity inflection points in the activity information and the length of the repeated activity path in the activity information.

[0135] The environmental impact degree value can be expressed as:

[0136] ;

[0137] Among them, represents the environmental impact degree value, represents the impact attribute parameter, represents the foraging behavior description value, and the foraging behavior description value can be expressed as: , where represents the length of the repeated activity path, and represents the number of activity inflection points.

[0138] When is larger, it indicates that the impact of the feces discharged by the livestock during activities in the i-th sub-region on this region is greater, and the excretion behavior of the livestock is modified through the foraging behavior of the livestock. The larger the foraging behavior description value of the livestock in the i-th sub-region, that is is larger, the more excretion behaviors it has, and the greater the impact on the environment of this region. Combining the impact attribute parameter of the livestock, calculate the final environmental impact degree value of the livestock on the i-th sub-region. When the environmental impact degree value is larger, it indicates that the impact degree of the livestock farming on the environment is greater.

[0139] Repeat the process of obtaining the environmental impact degree value to obtain the environmental impact degree value of the livestock farming on each sub-region.

[0140] Figure 7 The flowchart of the process for obtaining the pollution impact degree value provided by the seventh embodiment of the present invention. Determining the pollution impact degree value of the livestock farming on the environment according to each environmental impact degree value and the nitrogen and phosphorus contents of the sampling points in each sub-region includes:

[0141] S701. Multiply the environmental impact degree value of the i-th sub-region by the nitrogen and phosphorus contents of the sampling points in the i-th sub-region to obtain the pollution impact degree value of the i-th sub-region on the environment, where the value range of i is from 1 to the number of sub-regions.

[0142] The pollution impact degree value of the i-th sub-region on the environment can be expressed as: , where the represents the environmental impact degree value of the i-th sub-region, and the represents the nitrogen and phosphorus contents of the sampling points in the i-th sub-region.

[0143] S702. Repeat the process of obtaining the pollution impact degree value to obtain the pollution impact degree values of each sub-region on the environment.

[0144] S703. Add up the pollution impact degree values in sequence to obtain the pollution impact degree value of the livestock farming on the environment.

[0145] The pollution impact degree value of the livestock farming on the environment can be expressed as:

[0146] ;

[0147] where the represents the pollution impact degree value of the livestock farming on the environment, the represents the number of sub-regions, and the function is a prior art and will not be elaborated here.

[0148] The present invention has the following beneficial effects:

[0149] First, obtain the activity information of the livestock to be monitored, and divide the breeding area into at least two sub-areas. This is the data basis for subsequent analysis. Secondly, obtain the position parameters corresponding to the sub-area information, and obtain the influence attribute parameters according to the position parameters and the activity information. The position parameters are used as the weights for obtaining the influence attribute parameters and are positively correlated with the influence attribute parameters. The larger the influence attribute parameter, the greater the influence degree of the livestock on the area. Furthermore, obtain the confidence level of the excretion behavior time according to the activity information, and obtain the environmental impact degree value of livestock breeding on each sub-area according to the confidence level, the influence attribute parameter, and the activity information. Here, the environmental impact degree value of livestock breeding on each sub-area is obtained by combining the three aspects related to the current environmental impact of livestock breeding, namely the confidence level, the influence attribute parameter, and the activity information. Finally, determine the pollution impact degree value of the livestock breeding on the environment according to each environmental impact degree value and the nitrogen and phosphorus contents of the sampling points in each sub-area. By representing the environmental impact of livestock breeding on different sub-areas with different weights, that is, the environmental impact degree values, assigned to different sub-areas in the breeding area, the environmental impact of livestock breeding on the breeding area can be evaluated more precisely.

[0150] It should be noted that: the above sequence of the embodiments of the present invention is only for description and does not represent the advantages or disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0151] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. The key point of each embodiment is to illustrate the differences from other embodiments.

Claims

1. A method for monitoring environmental pollution information applicable to animal husbandry, characterized in that: The method comprises: Obtain the activity information of the livestock to be monitored and divide the breeding area into at least two sub-areas; The position parameter is obtained according to the sub-area information, and the influencing attribute parameter is obtained according to the position parameter and the activity information; wherein the influencing attribute parameter is obtained by: obtaining the residence time, total activity path length, repeated activity path length and number of activity inflection points of the livestock to be monitored in the i-th sub-area in the activity information, wherein the value range of i is 1 to the number of the sub-areas; after multiplying the position parameter, the residence time, the repeated activity path length and the number of activity inflection points in sequence, the influencing attribute parameter corresponding to the i-th sub-area is obtained by dividing by the total activity path length; Obtaining the confidence of the excretion behavior time according to the activity information, and obtaining the environmental impact degree value of animal husbandry on each of the sub-areas according to the confidence, the influencing attribute parameter, and the activity information; The pollution impact degree value of animal husbandry on the environment is determined according to each of the environmental impact degree values ​​and the nitrogen and phosphorus contents of the sampling points in each of the sub-areas.

2. The environmental pollution information monitoring method suitable for animal husbandry as claimed in claim 1, characterized in that: The obtaining of the position parameter according to the sub-region information includes: Obtain the total area of ​​the breeding area, the area of ​​the low-elevation area in the ith sub-area and the standard deviation of the elevation change, and the cumulative difference in elevation change between the ith sub-area and the adjacent sub-area, wherein the area of ​​the low-elevation area represents the area in the ith sub-area whose elevation is lower than the average of the elevation of the breeding area, the total area is equal to the sum of the areas of each sub-area, and the value range of i is 1 to the number of the sub-areas; Dividing the area of ​​the region by the total area and then multiplying by the cumulative difference to obtain a first multiplier; After adding the first preset value to the standard deviation, the reciprocal is taken to obtain a second multiplier; The first multiplier and the second multiplier are multiplied together as an input value of a Sigmoid function, and an output value of the Sigmoid function is used as the position parameter corresponding to the i-th sub-region; The process of obtaining the position parameters is repeated to obtain the position parameters corresponding to each sub-region.

3. The environmental pollution information monitoring method suitable for animal husbandry as claimed in claim 1, characterized in that: The confidence level of the defecation behavior time obtained according to the activity information includes: Obtaining the duration of each stay of the livestock to be monitored on the activity path in the i-th sub-area in the activity information, and clustering the stay duration as data points to obtain a preset number of clusters, wherein the value range of i is 1 to the number of the sub-areas; The cluster corresponding to the data point with the smallest average value is the excretion behavior time cluster; The confidence level that each of the stay durations is the excretion behavior time is obtained according to the activity information and the excretion behavior time cluster.

4. The environmental pollution information monitoring method suitable for animal husbandry as claimed in claim 3, characterized in that: Acquiring the confidence that each of the stay durations is the excretion behavior time according to the activity information and the excretion behavior time cluster includes: Obtain the number of the stay durations in the excretion behavior time cluster that are the same as the vth stay duration as a first number, and obtain the total number of the stay durations in the excretion behavior time cluster, wherein the value range of v is 1 to the number of the stay durations in the excretion behavior time cluster; Acquire a first speed of the livestock to be monitored before the vth stay duration and a second speed of the livestock to be monitored after the vth stay duration in the activity information; The second speed is subtracted from the first speed and then divided by the first speed to obtain a speed change value; The opposite of the absolute value of the speed change value is used as the input value of the exponential function; The first number is divided by the total number and then multiplied by the output value of the exponential function to serve as the input value of the Sigmoid function, and the output value of the Sigmoid function is the confidence that the vth duration of the stay is the time of the excretion behavior; The confidence acquisition process is repeated to obtain the confidence that each dwelling duration is the excretion behavior time.

5. The environmental pollution information monitoring method suitable for animal husbandry as claimed in claim 3, characterized in that: Obtaining the environmental impact value of animal husbandry on each sub-area according to the confidence, the impact attribute parameter, and the activity information includes: Obtaining the vth stay duration in the excretion behavior time cluster and the vth confidence that the vth stay duration is the excretion behavior time, wherein the value range of v is 1 to the number of the stay durations in the excretion behavior time cluster; After multiplying the vth stay duration by the vth confidence level, the resultant multiplication is divided by the total stationary time of the livestock to be monitored in the i-th sub-area to obtain a third multiplier corresponding to the vth stay duration; Repeat the process of obtaining the third multiplier to obtain the third multiplier corresponding to each of the stay durations in the defecation behavior time cluster, and add the third multipliers in sequence to obtain a total multiplier value; The total value of the multiplier, the influencing attribute parameter and the foraging behavior description value are multiplied in sequence as the input value of the Sigmoid function, and the output value of the Sigmoid function is the environmental impact degree value of the animal husbandry on the i-th sub-area, wherein the foraging behavior description value is the product of the number of activity inflection points in the activity information and the length of the repeated activity path in the activity information; The process of obtaining the environmental impact value is repeated to obtain the environmental impact value of the animal husbandry on each of the sub-areas.

6. The environmental pollution information monitoring method suitable for animal husbandry as claimed in claim 3, characterized in that: Clustering the stay duration as data points to obtain a preset number of clusters includes: The K-means algorithm is used to cluster the data points to obtain a preset number of clusters, the residence duration is used as the data point, and the preset number includes two.

7. The environmental pollution information monitoring method suitable for animal husbandry as claimed in claim 1, characterized in that: Determining the pollution impact value of animal husbandry on the environment according to each of the environmental impact values ​​and the nitrogen and phosphorus content of the sampling points in each of the sub-areas includes: Obtain the environmental impact value of the ith sub-region and multiply it by the nitrogen and phosphorus content of the sampling point in the ith sub-region to obtain the pollution impact value of the ith sub-region on the environment, wherein the value range of i is 1 to the number of the sub-regions; Repeat the process of obtaining the pollution impact degree value to obtain the pollution impact degree value of each sub-area on the environment; The pollution impact degree values ​​of each are added up in sequence to obtain the pollution impact degree value of the livestock breeding on the environment.

8. The environmental pollution information monitoring method suitable for animal husbandry as claimed in claim 1, characterized in that: The dividing of the breeding area into at least two sub-areas comprises: A satellite image of the breeding area is obtained, and the satellite image is divided into at least two sub-areas using a grid sampling method.

9. The environmental pollution information monitoring method suitable for animal husbandry as claimed in claim 1, characterized in that: The livestock to be monitored includes sheep.

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