A self-learning-based livestock farming environment control system

Abstract

This invention relates to the field of environmental monitoring technology, and more particularly to a self-learning-based livestock farming environmental control system. In this invention, a multi-point monitoring method is used to acquire ammonia concentration data at multiple points. The points to be monitored are marked according to their ammonia concentrations. Points with excessively high ammonia concentrations are marked as Level 3 points. The type of the point to be monitored is determined a second time based on the slope of the ammonia concentration-time curve at the current time node. When the slope is high, considering that the ammonia concentration is likely to increase in a short period, the point to be monitored is marked as a Level 3 point. The number of points of each type is counted. The ammonia concentration in the livestock farming environment is comprehensively analyzed based on the proportion of Level 3 points. When the proportion of Level 3 points is high, the corresponding treatment method is determined in a timely manner to reduce the ammonia concentration, thus matching the farming environment with the ammonia monitoring method, effectively controlling the ammonia concentration in the livestock farming environment, and improving environmental safety.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring technology, and in particular to a self-learning-based livestock farming environmental control system. Background Technology

[0002] Ammonia is irritating. When the concentration of ammonia in the breeding environment is too high, it will irritate the respiratory mucosa of animals, reduce their respiratory defense capabilities, and make them more susceptible to respiratory infections, pneumonia, and other diseases. By monitoring the concentration of ammonia and taking timely measures, the incidence of respiratory diseases in animals can be reduced, ensuring their healthy growth. Current technology uses a PC to process and analyze data collected by individual monitoring devices and environmental monitoring devices to achieve real-time monitoring. However, changes in ammonia concentration are affected by a variety of factors, and applying the same treatment method to different livestock breeding environments can easily lead to untimely ammonia removal.

[0003] Chinese Patent Application No. CN201510817560.0 discloses a livestock breeding monitoring system, including an environmental monitoring device and individual monitoring devices. The environmental monitoring device includes temperature and humidity sensors, light sensors, carbon dioxide sensors, ammonia sensors, a fan, and lighting devices. These sensors are all connected to a main controller via electrical conductors. The individual monitoring devices include a GPS positioning device and a vital signs detection device. The main controller is connected to an alarm via an electrical conductor and to a PC via a data cable. This livestock breeding monitoring system comprehensively monitors various factors, enabling early detection and resolution of diseases. Furthermore, by using a PC to process and analyze the data collected by the individual and environmental monitoring devices, it achieves real-time online monitoring and intelligent control of livestock breeding environment information.

[0004] However, existing technologies still have the following problems:

[0005] The concentration of ammonia is affected by a variety of factors, and applying the same treatment method to different livestock farming environments can easily lead to untimely ammonia discharge. Summary of the Invention

[0006] Therefore, this invention provides a self-learning-based livestock farming environment control system to overcome the problem in the prior art that the change of ammonia concentration is affected by multiple factors, and that applying the same treatment method to different livestock farming environments can easily lead to untimely ammonia discharge.

[0007] To achieve the above objectives, this invention provides a self-learning-based livestock farming environment control system. It includes:

[0008] The data acquisition module includes sensors installed at several test points in the livestock farming environment to collect the ammonia concentration at the corresponding points.

[0009] A plotting module, which is connected to the acquisition module, is used to plot an ammonia concentration-time curve based on the ammonia concentration at each of the acquired test points.

[0010] A marking module, which is connected to the acquisition module and the drawing module respectively, is used to mark each of the test points based on the measured ammonia concentration and count the number of marked points of each type.

[0011] The data analysis module, which is connected to the acquisition module, the plotting module, and the marking module, is used to conduct a preliminary analysis based on the proportion of the marked tertiary points to determine whether the monitoring of ammonia concentration in the livestock breeding environment is qualified. If the monitoring of ammonia concentration in the livestock breeding environment is initially determined to be unqualified, a secondary determination is made based on the temporal dispersion of ammonia concentration at each of the test points at the current time node to determine whether the monitoring is qualified. Alternatively, the module can analyze the processing method of the ammonia concentration monitoring process based on the proportion of the tertiary points.

[0012] Furthermore, the marking module is used to mark the test point based on the ammonia concentration of a single test point at the current time node, including:

[0013] If the ammonia concentration is less than or equal to the first preset ammonia concentration, the marking module determines to mark the test point as a first-level point.

[0014] If the ammonia concentration is greater than the first preset ammonia concentration and less than or equal to the second preset ammonia concentration, the marking module determines the type of the test point based on the ammonia concentration-time curve of the test point.

[0015] If the ammonia concentration is greater than the second preset ammonia concentration, the marking module determines to mark the test point as a level 3 point.

[0016] Furthermore, the marking module is used to perform a secondary determination of the type of the test point based on the ammonia concentration-time curve of the test point, including:

[0017] Calculate the slope of the ammonia concentration-time curve at the current time point for the measured location.

[0018] If the slope is greater than or equal to the preset slope, the marking module determines to mark the point to be measured as a level 3 point.

[0019] If the slope is less than the preset slope, the marking module determines to mark the point to be measured as a secondary point.

[0020] Furthermore, the data analysis module is used to conduct a preliminary analysis based on the proportion of marked tertiary monitoring points to determine whether the monitoring of ammonia concentration in the livestock farming environment is up to standard, including:

[0021] If the proportion of the number of the three-level points is greater than or equal to the first preset proportion of the number of the three-level points, the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, and analyzes the handling method for the ammonia concentration monitoring process based on the proportion of the number of the three-level points.

[0022] If the proportion of the number of the three-level points is less than the proportion of the first preset three-level points and greater than or equal to the proportion of the second preset three-level points, the data analysis module initially determines that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, and makes a secondary determination on whether the monitoring is qualified based on the time domain dispersion of ammonia concentration at each of the test points at the current time node.

[0023] If the proportion of the number of the three-level monitoring points is less than the second preset proportion of the number of the three-level monitoring points, then the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is qualified.

[0024] Furthermore, the data analysis module is used to perform a secondary judgment on whether the monitoring is qualified based on the time-domain dispersion of the ammonia concentration at each of the test points at the current time node, including:

[0025] Calculate the variance of ammonia concentration at each of the measured points at the current time node to obtain the time-domain dispersion.

[0026] If the time-domain dispersion is greater than or equal to the preset time-domain dispersion, the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, and analyzes the processing method for the ammonia concentration monitoring process based on the proportion of the number of three-level points.

[0027] If the time-domain dispersion is less than the preset time-domain dispersion, the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is qualified and determines to adjust the ventilation frequency to the corresponding value.

[0028] Furthermore, the data analysis module is used to adjust the ventilation frequency to a corresponding value based on the time-domain dispersion, wherein,

[0029] The increase in ventilation frequency is positively correlated with the time-domain dispersion.

[0030] Furthermore, the data analysis module is used to analyze the processing method for ammonia concentration monitoring based on the proportion of the three-level monitoring points, including:

[0031] Calculate the difference between the proportion of third-level locations and the first preset proportion of third-level locations.

[0032] If the difference is greater than or equal to the first preset difference, the data analysis module determines that the feces cleaning is not timely and adjusts the feces cleaning frequency based on the proportion of secondary points.

[0033] If the difference is less than the first preset difference and greater than or equal to the second preset difference, the data analysis module determines the reason for the failure of ammonia concentration monitoring in the livestock breeding environment based on the distribution of the three-level points.

[0034] If the difference is less than the second preset difference, the data analysis module determines to adjust the ventilation duration based on the proportion of primary points.

[0035] Furthermore, the data analysis module is used to adjust the frequency of fecal cleaning based on the proportion of secondary locations, wherein,

[0036] The increase in the frequency of fecal cleaning is positively correlated with the proportion of secondary collection points.

[0037] Furthermore, the data analysis module is used to analyze the reasons for the failure of ammonia concentration monitoring in livestock farming environments based on the distribution of the three-level monitoring points, including:

[0038] If the distribution of the three-level monitoring points is concentrated, the data analysis module determines that the reason for the failure to monitor the ammonia concentration in the livestock breeding environment is that the manure is not cleaned up in time, and adjusts the frequency of manure cleaning based on the proportion of the two-level monitoring points.

[0039] If the distribution of the three-level monitoring points is scattered, the data analysis module determines that the reason for the failure to monitor the ammonia concentration in the livestock breeding environment is that the individual density does not meet the standard, and issues a transfer notice to correct the number of individuals in the monitoring area.

[0040] Furthermore, the data analysis module is used to adjust the ventilation duration based on the proportion of primary monitoring points, wherein,

[0041] The increase in ventilation duration is negatively correlated with the proportion of primary ventilation points.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention uses a multi-point monitoring method to obtain ammonia concentration data at multiple points, marks the test points according to the ammonia concentration at each point, marks the test points with excessively high ammonia concentrations as level 3 points, counts the number of each type of point, and comprehensively analyzes the ammonia concentration in the livestock breeding environment based on the proportion of level 3 points. When the proportion of level 3 points is high, the corresponding treatment method is determined in a timely manner, thereby reducing the ammonia concentration in a timely manner, so that the breeding environment matches the ammonia monitoring method, thereby effectively controlling the ammonia concentration in the livestock breeding environment and improving environmental safety.

[0043] Furthermore, in this invention, when the ammonia concentration is between the first preset ammonia concentration and the second preset ammonia concentration, the type of the test point is determined twice based on the slope of the current time node in the ammonia concentration-time curve. When the slope is high, considering that the ammonia concentration is likely to increase in a short period of time, the test point is marked as a level 3 point, thereby improving the control precision for each test point and improving the analysis accuracy of ammonia concentration in the aquaculture environment.

[0044] Furthermore, in this invention, the distribution of ammonia sources in the aquaculture environment is analyzed based on the time-domain dispersion of ammonia concentration at each test point to determine whether the distribution is uniform. Then, the treatment method for the aquaculture environment is determined based on the time-domain dispersion. When the time-domain dispersion is small, it is determined that the distribution of ammonia sources is relatively uniform, and the ventilation batch is increased, thereby increasing the rate of ammonia concentration reduction and improving environmental safety. Attached Figure Description

[0045] Figure 1 This is a structural block diagram of the self-learning livestock farming environment control system of the present invention.

[0046] Figure 2 Flowchart for determining the type of the point to be measured;

[0047] Figure 3 The flowchart for determining the type of the point to be measured in the secondary determination;

[0048] Figure 4 This is a flowchart for preliminary analysis of the determination of whether the monitoring of ammonia concentration in livestock farming environments is up to standard. Detailed Implementation

[0049] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0050] It should be noted that the data in this embodiment are all derived from a comprehensive analysis and evaluation of historical data from the six months prior to this determination and the corresponding historical determination results by the system described in this invention. Those skilled in the art will understand that the system described in this invention can determine the above-mentioned parameters for a single item by selecting the value with the highest proportion based on the data distribution as the preset standard parameter, using weighted summation to obtain the value as the preset standard parameter, substituting each historical data point into a specific formula and using the value obtained by that formula as the preset standard parameter, or other selection methods, as long as the system described in this invention can clearly define different specific situations in the single-item determination process through the obtained values.

[0051] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0052] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0053] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0054] Please see Figure 1 As shown, it is a structural block diagram of the self-learning livestock breeding environment control system of the present invention.

[0055] The self-learning-based livestock farming environment control system provided in this embodiment includes:

[0056] The data acquisition module includes sensors installed at several test points in the livestock farming environment to collect the ammonia concentration at the corresponding points.

[0057] A plotting module, which is connected to the acquisition module, is used to plot an ammonia concentration-time curve based on the ammonia concentration at each of the acquired test points.

[0058] A marking module, which is connected to the acquisition module and the drawing module respectively, is used to mark each of the test points based on the measured ammonia concentration and count the number of marked points of each type.

[0059] The data analysis module, which is connected to the acquisition module, the plotting module, and the marking module, is used to conduct a preliminary analysis based on the proportion of the marked tertiary points to determine whether the monitoring of ammonia concentration in the livestock breeding environment is qualified. If the monitoring of ammonia concentration in the livestock breeding environment is initially determined to be unqualified, a secondary determination is made based on the temporal dispersion of ammonia concentration at each of the test points at the current time node to determine whether the monitoring is qualified. Alternatively, the module can analyze the processing method of the ammonia concentration monitoring process based on the proportion of the tertiary points.

[0060] This invention employs multi-point monitoring to acquire ammonia concentration data at multiple locations. Based on the ammonia concentration at each location, the monitoring points are marked. Points with excessively high ammonia concentrations are designated as Level 3 points. The number of points of each type is counted, and the ammonia concentration in the livestock farming environment is comprehensively analyzed based on the proportion of Level 3 points. When the proportion of Level 3 points is high, corresponding treatment methods are promptly determined to reduce the ammonia concentration. This ensures that the farming environment matches the ammonia monitoring method, effectively controlling the ammonia concentration in the livestock farming environment and improving environmental safety.

[0061] Please see Figure 2 As shown, it is a flowchart for determining the type of the point to be measured.

[0062] Specifically, the marking module is used to mark the test point based on the ammonia concentration of a single test point at the current time point, including:

[0063] If the ammonia concentration is less than or equal to the first preset ammonia concentration, the marking module determines to mark the test point as a first-level point.

[0064] If the ammonia concentration is greater than the first preset ammonia concentration and less than or equal to the second preset ammonia concentration, the marking module determines the type of the test point based on the ammonia concentration-time curve of the test point.

[0065] If the ammonia concentration is greater than the second preset ammonia concentration, the marking module determines to mark the test point as a level 3 point.

[0066] Specifically, in this embodiment, the first preset ammonia concentration and the second preset ammonia concentration are obtained by prior measurement. The highest ammonia concentration in several qualified livestock breeding environments is obtained, and the average ammonia concentration is calculated. The first preset ammonia concentration is 0.7 to 0.8 times the average ammonia concentration, and the second preset ammonia concentration is 0.9 to 0.95 times the average ammonia concentration.

[0067] Please see Figure 3 As shown, it is a flowchart for determining the type of the point to be measured in a secondary determination.

[0068] Specifically, the marking module is used to perform a secondary determination of the type of the test point based on the ammonia concentration-time curve of the test point, including:

[0069] Calculate the slope of the ammonia concentration-time curve at the current time point for the measured location.

[0070] If the slope is greater than or equal to the preset slope, the marking module determines to mark the point to be measured as a level 3 point.

[0071] If the slope is less than the preset slope, the marking module determines to mark the point to be measured as a secondary point.

[0072] Specifically, in this embodiment, the preset slope is obtained from a pre-measured data. Ammonia concentration change data in several livestock breeding environments with qualified air quality are obtained, and ammonia concentration-time curves are plotted respectively. The time interval from the end of the last ventilation to the current time node in the current ammonia concentration-time curve is determined. Based on the time interval, the corresponding time node in each curve is selected, the slope at each selected time node is determined, the average slope is calculated, and the preset slope is obtained.

[0073] In this invention, when the ammonia concentration is between the first preset ammonia concentration and the second preset ammonia concentration, the type of the test point is determined twice based on the slope of the current time node in the ammonia concentration-time curve. When the slope is high, considering that the ammonia concentration is likely to increase in a short time, the test point is marked as a level 3 point, thereby improving the control precision for each test point and improving the analysis accuracy of ammonia concentration in the aquaculture environment.

[0074] Please see Figure 4 As shown, it is a flowchart for preliminary analysis of whether the monitoring of ammonia concentration in the livestock breeding environment is qualified.

[0075] Specifically, the data analysis module is used to conduct a preliminary analysis based on the proportion of marked tertiary monitoring points to determine whether the monitoring of ammonia concentration in the livestock farming environment is up to standard, including:

[0076] If the proportion of the number of the three-level points is greater than or equal to the first preset proportion of the number of the three-level points, the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, and analyzes the handling method for the ammonia concentration monitoring process based on the proportion of the number of the three-level points.

[0077] If the proportion of the number of the three-level points is less than the proportion of the first preset three-level points and greater than or equal to the proportion of the second preset three-level points, the data analysis module initially determines that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, and makes a secondary determination on whether the monitoring is qualified based on the time domain dispersion of ammonia concentration at each of the test points at the current time node.

[0078] If the proportion of the number of the three-level monitoring points is less than the second preset proportion of the number of the three-level monitoring points, then the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is qualified.

[0079] Specifically, in this embodiment, the first preset three-level quantity ratio is selected between the interval [0.5, 0.55], and the second preset three-level quantity ratio is selected between the interval [0.3, 0.35].

[0080] Specifically, the data analysis module is used to perform a secondary judgment on whether the monitoring is qualified based on the time-domain dispersion of the ammonia concentration at each of the test points at the current time point, including:

[0081] Calculate the variance of ammonia concentration at each of the measured points at the current time node to obtain the time-domain dispersion.

[0082] If the time-domain dispersion is greater than or equal to the preset time-domain dispersion, the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, and analyzes the processing method for the ammonia concentration monitoring process based on the proportion of the number of three-level points.

[0083] If the time-domain dispersion is less than the preset time-domain dispersion, the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is qualified and determines to adjust the ventilation frequency to the corresponding value.

[0084] Specifically, in this embodiment, the preset time-domain dispersion is obtained by pre-measurement. Ammonia concentration data in several livestock breeding environments with qualified air quality are obtained. Ammonia concentration data of each test point before ventilation is extracted. The variance of ammonia concentration at each test point in each livestock breeding environment is calculated. The mean variance is calculated to obtain the preset dispersion.

[0085] In this invention, the distribution of ammonia sources in the aquaculture environment is analyzed based on the time-domain dispersion of ammonia concentration at each test point to determine whether the distribution is uniform. Then, the treatment method for the aquaculture environment is determined based on the time-domain dispersion. When the time-domain dispersion is small, it is determined that the distribution of ammonia sources is relatively uniform, and the ventilation batch is increased, thereby increasing the rate of ammonia concentration reduction and improving environmental safety.

[0086] Specifically, the data analysis module is used to adjust the ventilation frequency to a corresponding value based on the time-domain dispersion, wherein,

[0087] The increase in ventilation frequency is positively correlated with the time-domain dispersion.

[0088] In this embodiment, optionally,

[0089] The time-domain discreteness is compared with the first preset time-domain discreteness and the second preset time-domain discreteness.

[0090] If the time-domain dispersion is less than or equal to the first preset time-domain dispersion, the first ventilation frequency is increased to 0.1 times the initial ventilation frequency.

[0091] If the time-domain dispersion is greater than the first preset time-domain dispersion and less than or equal to the second preset time-domain dispersion, then the second ventilation frequency is increased to 0.2 times the initial ventilation frequency.

[0092] If the time-domain dispersion is greater than the second preset time-domain dispersion, then the third ventilation frequency is increased to 0.25 times the initial ventilation frequency.

[0093] The first preset time-domain dispersion is 0.7 to 0.72 times the preset time-domain dispersion, and the second preset time-domain dispersion is 0.8 to 0.82 times the preset time-domain dispersion.

[0094] Specifically, the data analysis module is used to analyze the processing method for ammonia concentration monitoring based on the proportion of three-level monitoring points, including:

[0095] Calculate the difference between the proportion of third-level locations and the first preset proportion of third-level locations.

[0096] If the difference is greater than or equal to the first preset difference, the data analysis module determines that the feces cleaning is not timely and adjusts the feces cleaning frequency based on the proportion of secondary points.

[0097] If the difference is less than the first preset difference and greater than or equal to the second preset difference, the data analysis module determines the reason for the failure of ammonia concentration monitoring in the livestock breeding environment based on the distribution of the three-level points.

[0098] If the difference is less than the second preset difference, the data analysis module determines to adjust the ventilation duration based on the proportion of primary points.

[0099] Specifically, in this embodiment, the first preset difference is 0.05 times the proportion of the first preset three-level quantity, and the second preset difference is 0.1 times the proportion of the first preset three-level quantity.

[0100] Specifically, the data analysis module is used to adjust the frequency of fecal cleaning based on the proportion of secondary locations, wherein,

[0101] The increase in the frequency of fecal cleaning is positively correlated with the proportion of secondary collection points.

[0102] In this embodiment, optionally,

[0103] The proportion of secondary locations is compared with the first preset proportion of secondary locations and the second preset proportion of secondary locations.

[0104] If the proportion of secondary points is less than or equal to the first preset proportion of secondary points, the first cleaning frequency is increased to 0.1 times the initial cleaning frequency.

[0105] If the proportion of secondary points is greater than the first preset proportion of secondary points and less than or equal to the second preset proportion of secondary points, then the second cleaning frequency is increased to 0.15 times the initial cleaning frequency.

[0106] If the proportion of secondary points is greater than the second preset proportion of secondary points, then the third cleaning frequency will be increased to 0.2 times the initial cleaning frequency.

[0107] The first preset secondary quantity ratio is selected between the range [0.15, 0.2], and the second preset secondary quantity ratio is selected between the range [0.25, 0.3].

[0108] Specifically, the data analysis module is used to analyze the reasons for unqualified monitoring of ammonia concentration in livestock farming environments based on the distribution of three-level monitoring points, including:

[0109] If the distribution of the three-level monitoring points is concentrated, the data analysis module determines that the reason for the failure to monitor the ammonia concentration in the livestock breeding environment is that the manure is not cleaned up in time, and adjusts the frequency of manure cleaning based on the proportion of the two-level monitoring points.

[0110] If the distribution of the three-level monitoring points is scattered, the data analysis module determines that the reason for the failure to monitor the ammonia concentration in the livestock breeding environment is that the individual density does not meet the standard, and issues a transfer notice to correct the number of individuals in the monitoring area.

[0111] Specifically, the data analysis module is used to adjust the ventilation duration based on the proportion of primary monitoring points.

[0112] The increase in ventilation duration is negatively correlated with the proportion of primary ventilation points.

[0113] In this embodiment, optionally,

[0114] The proportion of primary location points is compared with the proportion of the first preset number and the proportion of the second preset number.

[0115] If the proportion of primary points is less than or equal to the first preset proportion, the first ventilation duration is increased to 0.25 times the initial ventilation duration.

[0116] If the proportion of primary ventilation points is greater than the first preset proportion and less than or equal to the second preset proportion, then the second ventilation duration is increased to 0.2 times the initial ventilation duration.

[0117] If the proportion of primary ventilation points is greater than the proportion of the second preset number, then the third ventilation duration is increased to 0.1 times the initial ventilation duration.

[0118] Among them, the proportion of the first preset quantity is 1.1 times the proportion of the first preset three-level quantity, and the proportion of the second preset quantity is 1.2 times the proportion of the first preset three-level quantity.

[0119] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0120] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A self-learning-based livestock farming environment control system, characterized in that, include: The data acquisition module includes sensors installed at several test points in the livestock farming environment to collect the ammonia concentration at the corresponding points. A plotting module, which is connected to the acquisition module, is used to plot an ammonia concentration-time curve based on the ammonia concentration at each of the acquired test points. A marking module, which is connected to the acquisition module and the drawing module respectively, is used to mark each of the test points based on the measured ammonia concentration and count the number of marked points of each type. The data analysis module, which is connected to the acquisition module, the plotting module, and the marking module, is used to conduct a preliminary analysis based on the proportion of the number of marked tertiary points to determine whether the monitoring of ammonia concentration in the livestock breeding environment is qualified. If the monitoring of ammonia concentration in the livestock breeding environment is initially determined to be unqualified, a secondary determination is made based on the time-domain dispersion of ammonia concentration at each of the test points at the current time node to determine whether the monitoring is qualified, or the processing method of the ammonia concentration monitoring process is analyzed based on the proportion of the number of tertiary points. The marking module is used to mark the test point based on the ammonia concentration of a single test point at the current time node, including: If the ammonia concentration is less than or equal to the first preset ammonia concentration, the marking module determines to mark the test point as a first-level point. If the ammonia concentration is greater than the first preset ammonia concentration and less than or equal to the second preset ammonia concentration, the marking module determines the type of the test point based on the ammonia concentration-time curve of the test point. If the ammonia concentration is greater than the second preset ammonia concentration, the marking module determines to mark the test point as a level 3 point; The data analysis module is used to conduct a preliminary analysis based on the proportion of marked tertiary monitoring points to determine whether the monitoring of ammonia concentration in the livestock farming environment is up to standard, including: If the proportion of the number of the three-level points is greater than or equal to the first preset proportion of the number of the three-level points, the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, and analyzes the handling method for the ammonia concentration monitoring process based on the proportion of the number of the three-level points. If the proportion of the number of the three-level points is less than the proportion of the first preset three-level points and greater than or equal to the proportion of the second preset three-level points, the data analysis module initially determines that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, and makes a secondary determination on whether the monitoring is qualified based on the time domain dispersion of ammonia concentration at each of the test points at the current time node. If the proportion of the number of the three-level monitoring points is less than the second preset proportion of the number of the three-level monitoring points, then the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is qualified. Specifically, the distribution of ammonia sources in the aquaculture environment is analyzed based on the time-domain dispersion of ammonia concentration at each of the test points to determine whether the distribution is uniform and to determine the appropriate treatment method for the aquaculture environment.

2. The self-learning-based livestock farming environment control system according to claim 1, characterized in that, The marking module is used to perform a secondary determination of the type of the test point based on the ammonia concentration-time curve of the test point, including: Calculate the slope of the ammonia concentration-time curve at the current time point for the measured location. If the slope is greater than or equal to the preset slope, the marking module determines to mark the point to be measured as a level 3 point. If the slope is less than the preset slope, the marking module determines to mark the point to be measured as a secondary point.

3. The self-learning-based livestock farming environment control system according to claim 1, characterized in that, The data analysis module is used to make a secondary judgment on whether the monitoring is qualified based on the time-domain dispersion of the ammonia concentration at each of the test points at the current time node, including: Calculate the variance of ammonia concentration at each of the measured points at the current time node to obtain the time-domain dispersion. If the time-domain dispersion is greater than or equal to the preset time-domain dispersion, the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, and analyzes the processing method for the ammonia concentration monitoring process based on the proportion of the number of three-level points. If the time-domain dispersion is less than the preset time-domain dispersion, the data analysis module determines that the monitoring of ammonia concentration in the livestock breeding environment is qualified and determines to adjust the ventilation frequency to the corresponding value.

4. The self-learning-based livestock farming environment control system according to claim 3, characterized in that, The data analysis module is used to adjust the ventilation frequency to a corresponding value based on the time-domain dispersion, wherein, The increase in ventilation frequency is positively correlated with the time-domain dispersion.

5. The self-learning-based livestock farming environment control system according to claim 3, characterized in that, The data analysis module is used to analyze the processing methods for ammonia concentration monitoring based on the proportion of three-level monitoring points, including: Calculate the difference between the proportion of third-level locations and the first preset proportion of third-level locations. If the difference is greater than or equal to the first preset difference, the data analysis module determines that the feces cleaning is not timely and adjusts the feces cleaning frequency based on the proportion of secondary points. If the difference is less than the first preset difference and greater than or equal to the second preset difference, the data analysis module determines the reason for the failure of ammonia concentration monitoring in the livestock breeding environment based on the distribution of the three-level points. If the difference is less than the second preset difference, the data analysis module determines to adjust the ventilation duration based on the proportion of primary points.

6. The self-learning-based livestock farming environment control system according to claim 5, characterized in that, The data analysis module is used to adjust the frequency of fecal cleaning based on the proportion of secondary locations. The increase in the frequency of fecal cleaning is positively correlated with the proportion of secondary collection points.

7. The self-learning-based livestock farming environment control system according to claim 5, characterized in that, The data analysis module is used to analyze the reasons for the failure of ammonia concentration monitoring in livestock farming environments based on the distribution of three-level monitoring points, including: If the distribution of the three-level monitoring points is concentrated, the data analysis module determines that the reason for the failure to monitor the ammonia concentration in the livestock breeding environment is that the manure is not cleaned up in time, and adjusts the frequency of manure cleaning based on the proportion of the two-level monitoring points. If the distribution of the three-level monitoring points is scattered, the data analysis module determines that the reason for the failure to monitor the ammonia concentration in the livestock breeding environment is that the individual density does not meet the standard, and issues a transfer notice to correct the number of individuals in the monitoring area.

8. The self-learning-based livestock farming environment control system according to claim 5, characterized in that, The data analysis module is used to adjust ventilation duration based on the proportion of primary monitoring points. The increase in ventilation duration is negatively correlated with the proportion of primary ventilation points.

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