A method for intelligently controlling temperature and humidity in livestock breeding environment

Abstract

The present invention relates to the field of environmental control technology, and specifically to a method for intelligently controlling temperature and humidity in a livestock breeding environment. The present invention first obtains the initial abnormality of a monitoring point; obtains the livestock impact of the monitoring point according to the activity intensity of all livestock in the local area of ​​the monitoring point at the target time; obtains the actual environmental parameters of the breeding area at the target time according to the corresponding target abnormality of all monitoring points in the breeding area at the target time and the monitoring environmental parameters; and performs environmental control based on the actual environmental parameters of the breeding area at the target time. The present invention constructs actual environmental parameters that more accurately reflect the actual environment corresponding to the breeding area at the target time by deeply analyzing the degree to which the monitoring environmental parameters are affected by the environment, thereby improving the accuracy of environmental control.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental control, and in particular to a method for intelligently controlling temperature and humidity in a livestock breeding environment. Background Art

[0002] The livestock breeding environment is related to the health of livestock. The temperature and humidity of the livestock breeding environment are key environmental parameters that affect the growth of livestock and poultry. Appropriate temperature and humidity can reduce the stress response of animals, reduce the incidence of diseases, and improve feed conversion rate and growth rate. Modern animal husbandry is developing in the direction of scale and intelligence. Each breeding area of ​​large-scale farms needs to be intelligently controlled to improve management level and breeding effect.

[0003] In the process of animal husbandry, it is necessary to stabilize the temperature and humidity in a suitable range to ensure the breeding effect. The existing technology performs environmental control in the area to be controlled based on the temperature and humidity measured in the area to be controlled in the farm. However, since the activities of animal husbandry in the farm will cause airflow changes, the airflow changes will interfere with the accurate measurement of the temperature and humidity sensor, resulting in the test environment parameters being difficult to reflect the actual environment parameters, thus making the environmental control unreliable. Summary of the invention

[0004] In order to solve the technical problem that the existing technology is unreliable in environmental control, the purpose of the present invention is to provide a method for intelligently controlling the temperature and humidity of a livestock breeding environment. The technical solution adopted is as follows:

[0005] A method for intelligently controlling temperature and humidity in a livestock breeding environment, the method comprising:

[0006] Acquire a breeding data set and a spatial data set of a breeding area; the breeding data set includes monitoring environmental parameters corresponding to the monitoring points at each sampling time; the spatial data set includes the spatial position of each monitoring point and the spatial position of livestock at each sampling time;

[0007] The last sampling moment is taken as the target moment; the initial abnormality of the monitoring point is obtained according to the difference of the monitoring environment parameters of the monitoring point with the changes of the sampling moments and the prominence of the monitoring environment parameters of the monitoring point at the target moment; the activity intensity of the livestock is obtained according to the changes of the spatial positions of the livestock at the continuous sampling moments; the livestock impact of the monitoring point is obtained according to the activity intensity of all livestock in the local area of ​​the monitoring point at the target moment; the target abnormality of the monitoring point is obtained according to the initial abnormality and the livestock impact;

[0008] According to the target abnormality and the monitoring environmental parameters corresponding to all monitoring points in the breeding area at the target time, the actual environmental parameters of the breeding area at the target time are obtained; and environmental control is performed based on the actual environmental parameters of the breeding area at the target time.

[0009] Furthermore, the method for obtaining the initial abnormality degree includes:

[0010] In a preset time range of the target time, according to the difference of the monitoring environment parameters at all the sampling times of the monitoring point, the environmental stability index of the monitoring point is obtained;

[0011] Based on the prominence of the environmental stability index at the monitoring point compared to all monitoring points in the breeding area, obtaining a first parameter of environmental anomaly;

[0012] Based on the prominence of the monitoring environmental parameter at the monitoring point compared with all monitoring points in the breeding area at the target time, obtaining a second parameter of environmental anomaly;

[0013] The first environmental anomaly parameter and the second environmental anomaly parameter are forwardly fused to obtain an initial anomaly degree of the monitoring point.

[0014] Furthermore, the method for obtaining the environmental stability index includes:

[0015] In chronological order, the monitoring environment parameters corresponding to all sampling moments in the preset time range of the target moment are counted in sequence to obtain the overall monitoring environment parameter sequence at the target moment; the overall monitoring environment parameter sequence is segmented using the APCA algorithm to obtain each segmented subsequence and its segmented constant value; the mode of the monitoring environment parameter in the longest segmented subsequence is used as the standard environment value of the monitoring point;

[0016] The absolute value of the difference between the segmented constant value and the standard environmental value of each segmented subsequence is calculated to obtain the local difference parameter of the segmented subsequence; the mean of the local difference parameters of all segmented subsequences is calculated to obtain the first temperature fluctuation parameter; the ratio of the first temperature fluctuation parameter to the length of the longest segmented subsequence is calculated to obtain the second temperature fluctuation parameter; the second temperature fluctuation parameter is inversely normalized to obtain the environmental stability index of the monitoring point.

[0017] Furthermore, the method for obtaining the first parameter of the environmental anomaly includes:

[0018] The mean value of the environmental stability index of all monitoring points in the breeding area is calculated to obtain the regional stability index of the breeding area; the absolute value of the difference between the environmental stability index of the monitoring point and the regional stability index is calculated to obtain the first parameter of environmental anomaly.

[0019] Furthermore, the method for obtaining the second parameter of the environmental anomaly includes:

[0020] The mean of the monitoring environment parameters of all monitoring points in the breeding area is calculated to obtain the overall environmental index of the breeding area; the absolute value of the difference between the monitoring environment parameters of the monitoring points and the overall environmental index is calculated to obtain the second parameter of environmental anomaly.

[0021] Furthermore, the method for obtaining the activity intensity includes:

[0022] In the preset time interval of the target moment, the Euclidean distance between the spatial position of the livestock at each sampling moment and the spatial position at the previous sampling moment is taken as the displacement distance at the sampling moment; the mean of the displacement distances at all sampling moments is calculated to obtain the overall displacement parameter of the livestock;

[0023] The difference between the displacement distance at each sampling moment of animal husbandry and the displacement distance at the previous sampling moment is taken as the speed increase rate at the sampling moment; the mean of the speed increase rates at all sampling moments is calculated to obtain the overall speed increase parameter of animal husbandry;

[0024] The breeding data set also includes the weight of the livestock; the overall displacement parameter, the overall speed increase parameter and the weight of the livestock are forwardly integrated to obtain the activity intensity of the livestock.

[0025] Furthermore, the method for obtaining the livestock impact degree includes:

[0026] At the target moment, the Euclidean distance between the monitoring point and the livestock is obtained, and the livestock corresponding to the Euclidean distance less than the preset distance threshold is used as the reference livestock of the monitoring point; the Euclidean distance between the monitoring point and the livestock is inversely normalized to obtain the influence weight of the reference livestock, and the influence weights of all the reference livestock of the monitoring point are used to perform weighted summation on all the activity intensities to obtain the livestock influence of the monitoring point.

[0027] Furthermore, the method for obtaining the target abnormality degree includes:

[0028] The product of the initial abnormality degree and the livestock impact degree is calculated, and the product is normalized to obtain a target abnormality degree.

[0029] Furthermore, the method for obtaining the actual environmental parameters includes:

[0030] At the target time, each monitoring point whose target abnormality is less than the preset abnormality threshold is marked as a normal monitoring point; the monitoring environmental parameters corresponding to all the normal monitoring points are averaged to obtain the actual environmental parameters of the breeding area at the target time.

[0031] Furthermore, the monitored environmental parameters include temperature and humidity values.

[0032] The present invention has the following beneficial effects:

[0033] Considering that the monitoring environmental parameters at the target time may be disturbed by livestock, making it difficult for the monitoring environmental parameters at the target time to reflect the actual monitoring environmental parameters, directly regulating the environment based on the monitoring environmental parameters will make the environmental regulation inappropriate, resulting in livestock being in an unsuitable environment.

[0034] In order to control the environment of the latest breeding area, the last sampling time is taken as the target time. In order to analyze the measurement abnormality of the monitoring point at the target time, considering that the actual environmental parameters of all monitoring points in the breeding area are relatively close under normal circumstances, the initial abnormality is constructed to reflect the difference between the monitoring environmental parameters of the monitoring point and the breeding area to which it belongs. The larger the initial abnormality, the more different the corresponding environmental parameters of the monitoring point are from the breeding area to which it belongs, reflecting the greater the abnormality of the corresponding monitoring environmental parameters of the monitoring point at the target time. Considering that the movement and breathing of livestock in the breeding area will cause airflow interference, causing the monitoring environmental parameters to deviate from the actual environmental parameters, the intensity of livestock activity is constructed to reflect the intensity of livestock activity. Considering that the more intense the livestock activity, the greater the airflow interference, the greater the impact on the corresponding monitoring environmental parameters of the monitoring point. At the same time, considering that the closer the livestock is to the monitoring point, the greater the impact on the environmental parameters of the monitoring point, the livestock impact degree of the monitoring point is obtained. The greater the livestock impact degree, the greater the impact of the surrounding livestock on the monitoring point, which is more likely to cause the corresponding monitoring environmental parameters of the monitoring point to be abnormal at the target time. Combine the initial abnormality degree and livestock impact degree of the monitoring point to obtain the target abnormality of the monitoring point. The target abnormality comprehensively reflects the abnormal degree of the monitoring environment parameters at the monitoring point at the target time. Then the actual environmental parameters of the breeding area at the target time are obtained. The actual environmental parameters more accurately reflect the actual environment of the breeding area at the target time, thereby improving the accuracy of environmental control and better ensuring that livestock are in a suitable environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 A flow chart of a method for intelligently controlling temperature and humidity in a livestock breeding environment provided by one embodiment of the present invention;

[0037] Figure 2A flow chart of a method for obtaining an initial abnormality degree provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the intelligent control method of temperature and humidity in a livestock breeding environment proposed by the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0039] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0040] The specific scheme of the method for intelligently controlling temperature and humidity in a livestock breeding environment provided by the present invention is described in detail below with reference to the accompanying drawings.

[0041] The embodiment of the present invention provides a method for intelligently controlling temperature and humidity in a livestock breeding environment. Figure 1 , which shows a flow chart of a method for intelligently controlling temperature and humidity in a livestock breeding environment provided by an embodiment of the present invention, the method comprising the following steps:

[0042] Step S1: Acquire a breeding data set and a spatial data set of a breeding area; the breeding data set includes the corresponding monitoring environment parameters of the monitoring points at each sampling time; the spatial data set includes the spatial position of each monitoring point and the spatial position of livestock at each sampling time.

[0043] The main purpose of the present invention is to accurately regulate the livestock environment. First, the breeding data set and the spatial data set of the breeding area are obtained to provide data support for subsequent environmental regulation.

[0044] Considering that in large-scale livestock farms, in order to avoid livestock concentration, the farms are reasonably divided into multiple breeding areas and ensure that livestock cannot break through the breeding areas, and livestock breeding is carried out in each breeding area. Multiple monitoring points are set up in each breeding area to realize environmental monitoring, and each monitoring point is equipped with a temperature sensor and a humidity sensor; the breeding area is also equipped with environmental control equipment to control temperature and humidity, so that the breeding environment of the breeding area is stable in a suitable temperature and humidity range.

[0045] In order to detect the environmental conditions in the breeding area, the animal husbandry monitoring system is used to obtain the temperature and humidity values ​​corresponding to the breeding area at each sampling time. Specifically, in the breeding area, according to the preset sampling frequency, the temperature sensor equipped at the monitoring point is used to collect temperature, and the corresponding temperature value of each monitoring point at each sampling time is obtained; according to the preset sampling frequency, the humidity sensor equipped at the monitoring point is used to collect humidity, and the corresponding humidity value of each monitoring point at each sampling time is obtained. In one embodiment of the present invention, the temperature value and the humidity value are used as monitoring environment parameters.

[0046] In order to detect the spatial distribution of monitoring points and livestock in the breeding area, the livestock monitoring system is used to obtain the spatial position of each monitoring point in the breeding area and the spatial position of the livestock at each sampling time. Specifically, considering that in order to achieve accurate management of livestock, a locator is installed on each livestock, and the spatial position of the livestock at each sampling time can be obtained according to the preset sampling frequency. In order to detect the livestock conditions in the breeding area, considering that the livestock will be inspected regularly, the weight of each livestock is recorded in the livestock monitoring system. The monitoring environment parameters corresponding to each sampling time and the weight of the livestock are used as a breeding data set; the spatial position of each monitoring point and the spatial position of the livestock at each sampling time are used as a spatial data set. In one embodiment of the present invention, data sampling is performed by synchronous sampling, wherein the preset sampling frequency is set to 30 seconds / time.

[0047] It should be noted that, in order to facilitate calculation, all indicator data involved in the calculation in the embodiment of the present invention are preprocessed to eliminate the dimension effect. The specific means of eliminating the dimension effect are technical means well known to those skilled in the art and are not limited here.

[0048] In order to ensure that livestock is in a suitable environment, the temperature and humidity need to be regulated. The temperature and humidity regulation process is the same in the present invention. The environmental parameter is taken as an example in the present invention, that is, the temperature regulation of any breeding area is illustrated. Considering that the monitoring environmental parameters of the monitoring point at the target time will be disturbed by livestock, resulting in the monitoring environmental parameters at the target time being difficult to reflect the real monitoring environmental parameters, directly regulating the environment based on the monitoring environmental parameters will make the environmental regulation inappropriate, resulting in livestock being in an unsuitable environment. First, it is necessary to analyze the corresponding abnormality of the monitoring point.

[0049] Step S2: Take the last sampling moment as the target moment; obtain the initial abnormality of the monitoring point according to the differences in the monitoring environment parameters of the monitoring point as the sampling moments change, and the prominence of the monitoring environment parameters of the monitoring point at the target moment; obtain the activity intensity of the livestock according to the changes in the spatial position of the livestock at consecutive sampling moments; obtain the livestock impact of the monitoring point according to the activity intensity of all livestock in the local area of ​​the monitoring point at the target moment; obtain the target abnormality of the monitoring point according to the initial abnormality and the livestock impact.

[0050] In order to control the environment of the latest breeding area, the last sampling time is taken as the target time. In order to analyze the measurement abnormality of the monitoring point at the target time, considering that the actual environmental parameters of all monitoring points in the breeding area are relatively close under normal circumstances, the initial abnormality is constructed to reflect the difference between the monitoring environmental parameters of the monitoring point and the breeding area to which it belongs. The larger the initial abnormality, the more different the corresponding environmental parameters of the monitoring point are from the breeding area to which it belongs, reflecting the greater the abnormality of the corresponding monitoring environmental parameters of the monitoring point at the target time. Considering that the movement and breathing of livestock in the breeding area will cause airflow interference, causing the monitoring environmental parameters to deviate from the actual environmental parameters, the intensity of livestock activity is constructed to reflect the intensity of livestock activity. Considering that the more intense the livestock activity, the greater the airflow interference, the greater the impact on the corresponding monitoring environmental parameters of the monitoring point. At the same time, considering that the closer the livestock is to the monitoring point, the greater the impact on the environmental parameters of the monitoring point, the livestock impact degree of the monitoring point is obtained. The greater the livestock impact degree, the greater the impact of the surrounding livestock on the monitoring point, which is more likely to cause the corresponding monitoring environmental parameters of the monitoring point to be abnormal at the target time. Combine the initial abnormality degree and livestock impact degree of the monitoring point to obtain the target abnormality of the monitoring point. The target abnormality comprehensively reflects the abnormal degree of the monitoring environment parameters of the monitoring point at the target time.

[0051] For a preliminary analysis of the degree of measurement anomaly at the target time, refer to Figure 2 , which shows a flow chart of a method for obtaining an initial abnormality in one embodiment of the present invention. Preferably, in one embodiment of the present invention, the method for obtaining an initial abnormality includes:

[0052] Step S201: within a preset time range of a target time, the environmental stability index of a monitoring point is obtained according to the differences in monitoring environmental parameters at all sampling times of the monitoring point.

[0053] The environmental stability index reflects the stability of the environmental parameters of the monitoring point. The larger the environmental stability index is, the more stable the environmental parameters of the monitoring point are in the period before the target time.

[0054] Preferably, in one embodiment of the present invention, the method for obtaining the environmental stability index includes:

[0055] According to the time sequence, the corresponding monitoring environment parameters of all sampling moments in the preset time range of the target moment are counted in turn to obtain the overall monitoring environment parameter sequence of the target moment; the overall monitoring environment parameter sequence is segmented using the APCA algorithm to obtain each segmented subsequence and its segmented constant value; the mode of the monitoring environment parameter in the longest segmented subsequence is used as the standard environment value of the monitoring point;

[0056] Calculate the absolute value of the difference between the segment constant value of each segmented subsequence and the standard environmental value to obtain the local difference parameter of the segmented subsequence; calculate the mean of the local difference parameters of all segmented subsequences to obtain the first temperature fluctuation parameter; calculate the ratio of the first temperature fluctuation parameter to the length of the longest segmented subsequence to obtain the second temperature fluctuation parameter; inversely normalize the second temperature fluctuation parameter to obtain the environmental stability index of the monitoring point. It should be noted that the APCA algorithm (Adaptive Piecewise Constant Approximation) is a prior art well known to those skilled in the art, and the specific method is not introduced here. In one embodiment of the present invention, the method for obtaining the preset time range of the target moment is: the time range corresponding to the sampling moments that only include the preset number before the target moment is used as the preset time range of the target moment, where the preset number is 100, which can be set by the implementer according to the implementation scenario, and is not limited here. In one embodiment of the present invention, the method of inverse normalization is: the opposite number of the second temperature fluctuation parameter is used as the power of the exponential function with the natural constant as the base to obtain the negative correlation mapping result.

[0057] For the above steps, the monitoring environment parameters of all sampling moments within the preset time range of the target moment are counted to form a time series, that is, the overall monitoring environment parameter sequence. The overall monitoring environment parameter sequence is segmented using the APCA algorithm to obtain each segmented subsequence and its segmented constant value, which is helpful to identify the stable interval and mutation interval of the monitoring environment parameter change. The standard environment value represents the main stable state of the monitoring environment parameter in a period of time before the target moment. The first temperature fluctuation parameter represents the difference between the segmented constant value and the standard environment value, reflecting the degree of difference between the segmented subsequence and the stable state. Considering that the longer the length of the longest segmented subsequence is, the longer the duration of the stable state is, and then the second temperature fluctuation parameter is obtained by calculating the ratio of the first temperature fluctuation parameter to the length of the longest segmented subsequence; the second temperature fluctuation parameter reflects the degree of fluctuation of the monitoring environment parameter in a period of time before the target moment, and the second temperature fluctuation parameter is inversely normalized to obtain the environmental stability index. The larger the environmental stability index is, the more stable the environmental parameters of the monitoring point are in a period of time before the target moment.

[0058] In other embodiments of the present invention, the variance of the monitoring environment parameters corresponding to all sampling moments in the preset time range of the target moment can also be calculated, and the variance is inversely normalized to obtain the environmental stability index of the monitoring point, wherein the variance reflects the degree of fluctuation of the monitoring environment parameters in a period of time before the target moment. In one embodiment of the present invention, the inverse normalization method is: the inverse of the variance is used as the power of an exponential function with a natural constant as the base to obtain a negative correlation mapping result, that is, the variance is used as x, and the variance is inversely normalized using exp(-x), wherein exp( ) is an exponential function.

[0059] Step S202: Obtaining a first parameter of environmental anomaly based on the prominence of the environmental stability index of the monitoring point compared to all monitoring points in the breeding area.

[0060] Considering that the livestock farm is equipped with a ventilation system, the stability of the environmental parameters of all monitoring points in the breeding area is relatively close under normal circumstances. For example, the ventilation system allows the air to flow more evenly in the breeding area, and the temperature distribution of all monitoring points in the breeding area is relatively balanced, so that the temperature stability of each monitoring point a period of time before the target time is relatively similar, and the first parameter of environmental anomaly is obtained. The larger the first parameter of environmental anomaly, the more the environmental stability of the monitoring point deviates from the overall level of the region, and the more abnormal it is.

[0061] Preferably, in one embodiment of the present invention, the method for obtaining the first parameter of the environmental anomaly includes:

[0062] The mean of the environmental stability index of all monitoring points in the breeding area is calculated to obtain the regional stability index of the breeding area; the absolute value of the difference between the environmental stability index of the monitoring point and the regional stability index is calculated to obtain the first parameter of environmental anomaly.

[0063] For the above steps, the regional stability index reflects the overall level of environmental stability indicators of all monitoring points in the breeding area. The larger the first parameter of environmental anomaly is, the more the environmental stability of the monitoring point deviates from the overall level of the region, that is, the more prominent the environmental stability index of the monitoring point is compared with all monitoring points in the breeding area.

[0064] Step S203: Based on the prominence of the monitoring environment parameters of the monitoring point at the target time compared with all the monitoring points in the breeding area, obtain the second parameter of the environmental anomaly.

[0065] Considering that livestock farms are equipped with ventilation systems to maintain air circulation, the air flows more evenly in the breeding area, so that under normal circumstances, the environmental parameters of all monitoring points in the breeding area at the target time are relatively close, and the second parameter of environmental anomaly is obtained. The larger the second parameter of environmental anomaly, the more the monitoring environmental parameters of the monitoring point at the target time deviate from the overall level of the region, that is, the more abnormal it is.

[0066] Preferably, in one embodiment of the present invention, the method for obtaining the second parameter of the environmental anomaly includes:

[0067] The mean of the monitoring environmental parameters of all monitoring points in the breeding area is calculated to obtain the overall environmental index of the breeding area; the absolute value of the difference between the monitoring environmental parameters of the monitoring points and the overall environmental index is calculated to obtain the second parameter of environmental anomaly.

[0068] For the above steps, the overall environmental indicators reflect the overall level of the monitoring environmental parameters of all monitoring points in the breeding area at the target time. The larger the second parameter of the environmental anomaly is, the more the monitoring environmental parameters of the monitoring point at the target time deviate from the overall level of the region, that is, the more prominent the monitoring environmental parameters of the monitoring point are compared with all monitoring points in the breeding area at the target time.

[0069] Step S204: forwardly fuse the first parameter of the environmental anomaly and the second parameter of the environmental anomaly to obtain the initial abnormality degree of the monitoring point.

[0070] The larger the initial abnormality, the more different the corresponding environmental parameters of the monitoring point are from the breeding area to which it belongs, which preliminarily reflects the greater the abnormality of the corresponding monitoring environmental parameters of the monitoring point at the target time.

[0071] Preferably, in one embodiment of the present invention, the product of the first environmental anomaly parameter and the second environmental anomaly parameter is calculated to obtain the initial abnormality degree of the monitoring point.

[0072] At this point, the initial abnormality is obtained.

[0073] Considering that livestock activities may cause the monitored environmental parameters measured at the monitoring point to deviate from the actual environmental parameters, for example, livestock will generate more heat when exercising, and the heat dissipation will be relatively reduced when resting. If the livestock are active near the monitoring point, it will cause increased local heat dissipation, causing the monitored environmental parameters measured at the monitoring point to deviate from the actual environmental parameters. First, an activity intensity is constructed to reflect the activity intensity of the livestock at the target time. Preferably, in one embodiment of the present invention, the method for obtaining the activity intensity includes:

[0074] In the preset time interval of the target moment, the Euclidean distance between the spatial position of the livestock at each sampling moment and the spatial position at the previous sampling moment is taken as the displacement distance at the sampling moment; the mean of the displacement distances at all sampling moments is calculated to obtain the overall displacement parameter of the livestock;

[0075] The difference between the displacement distance of livestock at each sampling moment and the displacement distance at the previous sampling moment is taken as the speed increase rate at the sampling moment; the mean of the speed increase rates at all sampling moments is calculated to obtain the overall speed increase parameter of livestock;

[0076] The breeding data set also includes the weight of livestock; the overall displacement parameter, the overall speed increase parameter and the weight of livestock are forward integrated to obtain the activity intensity of livestock. In one embodiment of the present invention, the method for obtaining the preset time interval of the target moment is: the time range corresponding to the sampling moment that only includes the preset number of intervals before the target moment is used as the preset time interval of the target moment, wherein the number of preset intervals is 80, which can be set by the implementer according to the implementation scenario, and is not limited here.

[0077] For the above steps, the displacement distance reflects the change in the spatial position of livestock between the sampling moment and the previous sampling moment, and the displacement distances at all sampling moments are combined to obtain the overall displacement parameter of livestock. The overall displacement parameter of livestock reflects the overall displacement level of livestock. The larger the overall displacement parameter, the more intense the livestock activity; the speed increase rate reflects the increase in the speed of livestock between the sampling moment and the previous sampling moment, and the speed increase rate at all sampling moments is combined to obtain the overall increase parameter of livestock speed. The overall increase parameter of livestock speed reflects the overall speed improvement level of livestock. The larger the overall increase parameter of livestock speed, the more intense the livestock activity. Considering that the greater the weight of livestock, the greater the vibration caused when running, which means that the livestock activity is more intense; the three factors of livestock displacement overall parameter, speed overall increase parameter and weight are forwardly integrated to obtain an activity intensity that can fully reflect the intensity of livestock activities. The greater the activity intensity, the more intense the livestock activity.

[0078] Specifically, the method for obtaining the activity intensity of livestock includes: normalizing the overall speed increase parameter to obtain the normalized result of the overall speed increase parameter; calculating the product of the overall displacement parameter of the livestock, the normalized result and the body weight to obtain the activity intensity of the livestock. It should be noted that the normalization method used is: normalization is performed using the norm normalization function to limit the numerical range to between 0 and 1. Normalization is a technical means well known to those skilled in the art, and the selection of the normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here. The formula for activity intensity in one embodiment of the present invention includes:

[0079]

[0080] In the formula, Indicates the intensity of livestock activities. Indicates the weight of livestock; Parameter indicating the overall increase in the speed of livestock farming; represents the overall parameter of livestock displacement; Represents the normalization function.

[0081] In the formula for activity intensity, The larger it is, the greater the increase in the speed of animal husbandry, which means the more intense the animal husbandry activities are; The larger it is, the greater the distance the livestock moves, which means the more intense the livestock activities; The larger the value, the greater the vibration caused by the livestock running, which means the livestock activity is more intense. The three factors of livestock displacement overall parameter, speed overall increase parameter and weight are positively integrated to obtain an activity intensity that can fully reflect the intensity of livestock activity. The greater the activity intensity, the more intense the livestock activity.

[0082] In order to analyze the impact of livestock around the monitoring point, preferably, in one embodiment of the present invention, the method for obtaining the livestock impact includes:

[0083] At the target moment, the Euclidean distance between the monitoring point and the livestock is obtained, and the livestock corresponding to the Euclidean distance less than the preset distance threshold is used as the reference livestock of the monitoring point; the Euclidean distance between the monitoring point and the livestock is inversely normalized to obtain the influence weight of the reference livestock, and the influence weights of all reference livestock of the monitoring point are used to perform weighted summation on all activity intensities to obtain the livestock influence of the monitoring point. In one embodiment of the present invention, the preset distance threshold is 15, which can be set by the implementer according to the implementation scenario, and is not limited here. In one embodiment of the present invention, the method of inverse normalization is: the opposite of the Euclidean distance is used as the power of an exponential function with a natural constant as the base to obtain a negative correlation mapping result.

[0084] For the above steps, the reference livestock of the monitoring point represents the livestock around the monitoring point, reflecting the livestock whose activities have a significant impact on the monitoring point. For the selected reference livestock, considering that the more intense the livestock activities are, the greater the airflow interference will be, which will affect the corresponding monitoring environmental parameters of the monitoring point. At the same time, considering that the closer the reference livestock is to the monitoring point, the greater the impact on the environmental parameters of the monitoring point, the livestock impact of the monitoring point is obtained. The greater the livestock impact, the greater the impact of the livestock around the monitoring point, and the more likely it is to cause abnormalities in the corresponding monitoring environmental parameters of the monitoring point at the target time.

[0085] At this point, the livestock impact is obtained.

[0086] In order to comprehensively reflect the abnormality of the monitoring environment parameters of the monitoring point at the target time, the target abnormality of the monitoring point is obtained by combining the initial abnormality and livestock impact of the monitoring point. The target abnormality comprehensively reflects the abnormality of the monitoring environment parameters of the monitoring point at the target time. The larger the target abnormality, the more difficult it is for the corresponding measurement value of the monitoring point at the target time to reflect the true value. Preferably, in one embodiment of the present invention, the method for obtaining the target abnormality includes:

[0087] The product of the initial abnormality and the livestock impact is calculated, and the product is normalized to obtain the target abnormality. It should be noted that the normalization method is: normalization is performed using the norm normalization function to limit the value range to between 0 and 1. Normalization is a technical means well known to those skilled in the art, and the normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0088] Step S3: According to the target abnormality corresponding to all monitoring points in the breeding area at the target time and the monitoring environmental parameters, the actual environmental parameters of the breeding area at the target time are obtained; and the environment is regulated based on the actual environmental parameters of the breeding area at the target time.

[0089] The target abnormality of the monitoring point is obtained through the above steps to reflect the abnormality of the monitoring environment parameters of the monitoring point at the target time. According to the target abnormality and monitoring environment parameters corresponding to all monitoring points in the breeding area at the target time, the actual environment parameters of the breeding area at the target time are obtained. The actual environment parameters more accurately reflect the actual environment corresponding to the breeding area at the target time, thereby improving the accuracy of environmental control and better ensuring that livestock is in a suitable environment.

[0090] In order to analyze the actual environment of the breeding area at the target time, preferably, in one embodiment of the present invention, the method for obtaining the actual environment parameters includes:

[0091] At the target time, each monitoring point whose target abnormality is less than the preset abnormality threshold is marked as a normal monitoring point; the corresponding monitoring environmental parameters of all normal monitoring points in the breeding area are averaged to obtain the actual environmental parameters of the breeding area at the target time. In one embodiment of the present invention, the preset abnormality threshold is 0.72, and the implementer can set it according to the implementation scenario.

[0092] With regard to the above steps, considering that different monitoring points in the breeding area are affected by animal husbandry to different degrees, and thus the target abnormality of different monitoring points is different, by marking the normal monitoring points, the monitoring points whose test values ​​are abnormal due to animal husbandry activities are excluded. The monitoring environmental parameters corresponding to the normal monitoring points in the breeding area reflect the monitoring points that are less affected by animal husbandry activities and have a high degree of normality in the test values. The corresponding monitoring environmental parameters of all normal monitoring points in the breeding area are averaged to obtain the actual environmental parameters of the breeding area at the target time. The actual environmental parameters can more accurately reflect the overall environmental conditions of the breeding area at the target time.

[0093] In order to perform environmental regulation, preferably, in one embodiment of the present invention, the method for performing environmental regulation includes:

[0094] The actual environmental parameters of the breeding area at the target time are used as the input of the PID controller, and the PID control output control instructions are performed. It should be noted that PID control is a well-known technology, which is only briefly described here: In environmental control, PID control is a commonly used feedback control method for adjusting the output of the system to approach the desired set point.

[0095] Specifically, the control instructions output by the PID controller are sent to the environmental control equipment in the breeding area, and the environmental control equipment performs environmental control according to the received control instructions to ensure that the livestock is in a suitable environment.

[0096] In summary, the embodiment of the present invention provides an intelligent control method for temperature and humidity in a livestock breeding environment. The present invention first obtains the initial abnormality of a monitoring point; obtains the livestock impact of a monitoring point according to the activity intensity of all livestock in the local area of ​​the monitoring point at the target time; obtains the actual environmental parameters of the breeding area at the target time according to the corresponding target abnormality of all monitoring points in the breeding area at the target time and the monitoring environmental parameters; and performs environmental control based on the actual environmental parameters of the breeding area at the target time. The present invention constructs actual environmental parameters that more accurately reflect the actual environment corresponding to the breeding area at the target time by deeply analyzing the degree to which the monitoring environmental parameters are affected by the environment, thereby improving the accuracy of environmental control.

[0097] It should be noted that the sequence of the above embodiments of the present invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying 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.

[0098] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for intelligently controlling temperature and humidity in a livestock breeding environment, characterized in that: The method comprises: Acquire a breeding data set and a spatial data set of a breeding area; the breeding data set includes monitoring environmental parameters corresponding to the monitoring points at each sampling time; the spatial data set includes the spatial position of each monitoring point and the spatial position of livestock at each sampling time; The last sampling moment is taken as the target moment; the initial abnormality of the monitoring point is obtained according to the difference of the monitoring environment parameters of the monitoring point with the changes of the sampling moments and the prominence of the monitoring environment parameters of the monitoring point at the target moment; the activity intensity of the livestock is obtained according to the changes of the spatial positions of the livestock at the continuous sampling moments; the livestock impact of the monitoring point is obtained according to the activity intensity of all livestock in the local area of ​​the monitoring point at the target moment; the target abnormality of the monitoring point is obtained according to the initial abnormality and the livestock impact; According to the target abnormality and the monitoring environment parameters corresponding to all monitoring points in the breeding area at the target time, the actual environment parameters of the breeding area at the target time are obtained; and the environment is regulated based on the actual environment parameters of the breeding area at the target time; The method for obtaining the initial abnormality degree includes: In a preset time range of the target time, according to the difference of the monitoring environment parameters at all the sampling times of the monitoring point, the environmental stability index of the monitoring point is obtained; Based on the prominence of the environmental stability index at the monitoring point compared to all monitoring points in the breeding area, obtaining a first parameter of environmental anomaly; Based on the prominence of the monitoring environmental parameter at the monitoring point compared with all monitoring points in the breeding area at the target time, obtaining a second parameter of environmental anomaly; Forward fusing the first environmental anomaly parameter and the second environmental anomaly parameter to obtain an initial anomaly degree of the monitoring point; The method for obtaining the activity intensity includes: In the preset time interval of the target moment, the Euclidean distance between the spatial position of the livestock at each sampling moment and the spatial position at the previous sampling moment is taken as the displacement distance at the sampling moment; the mean of the displacement distances at all sampling moments is calculated to obtain the overall displacement parameter of the livestock; The difference between the displacement distance at each sampling moment of animal husbandry and the displacement distance at the previous sampling moment is taken as the speed increase rate at the sampling moment; the mean of the speed increase rates at all sampling moments is calculated to obtain the overall speed increase parameter of animal husbandry; The breeding data set also includes the weight of the livestock; the overall displacement parameter, the overall speed increase parameter and the weight of the livestock are forward integrated to obtain the activity intensity of the livestock; The method for obtaining the livestock impact degree includes: At the target time, the Euclidean distance between the monitoring point and the livestock is obtained, and the livestock corresponding to the Euclidean distance less than the preset distance threshold is used as the reference livestock of the monitoring point; the Euclidean distance between the monitoring point and the livestock is inversely normalized to obtain the influence weight of the reference livestock, and the influence weights of all the reference livestock of the monitoring point are used to perform weighted summation on all the activity intensities to obtain the livestock influence of the monitoring point; The method for obtaining the target abnormality degree includes: Calculating the product of the initial abnormality and the livestock impact, normalizing the product, and obtaining a target abnormality; The method for obtaining the environmental stability index includes: In chronological order, the monitoring environment parameters corresponding to all sampling moments in the preset time range of the target moment are counted in sequence to obtain the overall monitoring environment parameter sequence at the target moment; the overall monitoring environment parameter sequence is segmented using the APCA algorithm to obtain each segmented subsequence and its segmented constant value; the mode of the monitoring environment parameter in the longest segmented subsequence is used as the standard environment value of the monitoring point; Calculate the absolute value of the difference between the segment constant value of each segment subsequence and the standard environment value to obtain the local difference parameter of the segment subsequence; calculate the mean value of the local difference parameters of all segment subsequences to obtain the first temperature fluctuation parameter; calculate the ratio of the first temperature fluctuation parameter to the length of the longest segment subsequence to obtain the second temperature fluctuation parameter; perform inverse normalization on the second temperature fluctuation parameter to obtain the environmental stability index of the monitoring point; The method for obtaining the first parameter of the environmental anomaly includes: Calculate the mean value of the environmental stability index of all monitoring points in the breeding area to obtain the regional stability index of the breeding area; calculate the absolute value of the difference between the environmental stability index of the monitoring point and the regional stability index to obtain the first parameter of environmental anomaly; The method for obtaining the second parameter of the environmental anomaly includes: The mean of the monitoring environment parameters of all monitoring points in the breeding area is calculated to obtain the overall environmental index of the breeding area; the absolute value of the difference between the monitoring environment parameters of the monitoring points and the overall environmental index is calculated to obtain the second parameter of environmental anomaly.

2. According to claim 1, a method for intelligently controlling temperature and humidity in a livestock breeding environment is characterized in that: The method for obtaining the actual environmental parameters includes: At the target time, each monitoring point whose target abnormality is less than the preset abnormality threshold is marked as a normal monitoring point; the monitoring environmental parameters corresponding to all the normal monitoring points are averaged to obtain the actual environmental parameters of the breeding area at the target time.

3. The method for intelligently controlling temperature and humidity in a livestock breeding environment according to claim 1, characterized in that: The monitored environmental parameters include temperature and humidity.

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