Livestock breeding environment control system based on self-learning

Abstract

The invention relates to the technical field of environment monitoring, in particular to a livestock breeding environment control system based on self-learning, which adopts a multi-point monitoring mode to obtain ammonia concentration data of a plurality of points, marks a to-be-detected point according to the ammonia concentration of each point, and obtains the ammonia concentration of the to-be-detected point according to the to-be-detected point. The method comprises the following steps: marking a to-be-detected point location with too high ammonia concentration as a third-level point location, secondarily judging the type of the to-be-detected point location based on the slope of a current time node in an ammonia concentration-time curve, marking the to-be-detected point location as the third-level point location when the slope is relatively high and the ammonia concentration is easy to increase in a short time, and counting the number of each type of point location. The ammonia concentration in the livestock breeding environment is comprehensively analyzed according to the number proportion of the third-level point locations, and the corresponding processing mode is determined in time when the number proportion of the third-level point locations is high, so that the ammonia concentration is reduced in time, the breeding environment is matched with the ammonia monitoring mode, the ammonia concentration in the livestock breeding environment is effectively controlled, and the livestock breeding efficiency is improved. And the environmental safety is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to a livestock breeding environment control system based on self-learning. Background Art

[0002] Ammonia is irritating. When the ammonia concentration in the breeding environment is too high, it will irritate the respiratory mucosa of animals and reduce the defense ability of the animal's respiratory tract, which can easily cause respiratory infections, pneumonia and other diseases. By monitoring the ammonia concentration and taking timely measures, the incidence of animal respiratory diseases can be reduced and the healthy growth of animals can be guaranteed. The existing technology uses a PC to organize and analyze the data collected by individual monitoring devices and environmental monitoring devices to achieve real-time monitoring effects. However, the change in ammonia concentration is affected by many factors. Taking the same treatment method for different livestock breeding environments can easily lead to untimely discharge of ammonia.

[0003] Chinese patent application number: CN201510817560.0 discloses a livestock breeding monitoring system, including an environmental monitoring device and an individual monitoring device, the environmental monitoring device includes a temperature and humidity sensor, a light sensor, a carbon dioxide sensor, an ammonia sensor, a fan and a lighting device, the temperature and humidity sensor, the light sensor, the carbon dioxide sensor, the ammonia sensor, the fan and the lighting device are all connected to a main controller through an electrical conductor, the individual monitoring device includes a GPS positioning device and a vital sign detection device, the main controller is connected to an alarm through an electrical conductor, and the main controller is connected to a PC through a data cable. The livestock breeding monitoring system monitors comprehensive factors, can discover and solve the disease as early as possible, and by using the PC to organize and analyze the data collected by the individual monitoring device and the environmental monitoring device, it realizes real-time online monitoring and intelligent control of livestock and poultry breeding environmental information.

[0004] However, the prior art still has the following problems:

[0005] The change of ammonia concentration is affected by many factors. Using the same treatment method for different livestock breeding environments can easily lead to untimely discharge of ammonia. Summary of the invention

[0006] To this end, the present invention provides a livestock breeding environment control system based on self-learning to overcome the problem in the prior art that the change of ammonia concentration is affected by multiple factors and that the same treatment method is adopted for different livestock breeding environments, which easily leads to untimely discharge of ammonia.

[0007] To achieve the above purpose, the present invention provides a livestock breeding environment control system based on self-learning. It includes:

[0008] A collection module, which includes sensors arranged at a number of points to be measured in the livestock breeding environment, for collecting ammonia concentrations at corresponding points;

[0009] A drawing module, connected to the acquisition module, for drawing an ammonia concentration-time curve based on the collected ammonia concentrations of each of the test points;

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

[0011] A data analysis module is respectively connected to the acquisition module, the drawing module and the marking module, and is used to preliminarily analyze whether the monitoring of ammonia concentration in the livestock breeding environment is qualified based on the proportion of the number of marked third-level points, and when it is preliminarily determined that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, a secondary determination is made on whether the monitoring is qualified based on the time domain discreteness of the ammonia concentration of each of the test points at the current time node, or a processing method for the ammonia concentration monitoring process is analyzed based on the proportion of the number of third-level points.

[0012] Furthermore, the marking module is used to mark the point to be measured based on the ammonia concentration of the single point to be measured 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 point to be measured 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 to perform a secondary determination on the type of the point to be measured based on the ammonia concentration-time curve of the point to be measured;

[0015] If the ammonia concentration is greater than the second preset ammonia concentration, the marking module determines to mark the point to be measured as a third-level point.

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

[0017] Calculate the slope of the ammonia concentration-time curve of the test point at the current time node,

[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 third-level 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 preliminarily analyze whether the monitoring of ammonia concentration in the livestock breeding environment is qualified based on the number ratio of the marked third-level points, including:

[0021] If the number ratio of the third-level points is greater than or equal to the first preset third-level number ratio, 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 number ratio of the third-level points;

[0022] If the proportion of the number of the third-level points is less than the first preset third-level proportion and greater than or equal to the second preset third-level proportion, the data analysis module preliminarily 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 discreteness of the ammonia concentration of each of the test points at the current time node;

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

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

[0025] Calculate the variance of the ammonia concentration at each of the test points at the current time node to obtain the time domain discreteness.

[0026] If the time domain discreteness is greater than or equal to the preset time domain discreteness, 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 number ratio of the third-level points;

[0027] If the time domain discreteness is less than the preset time domain discreteness, 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 a corresponding value.

[0028] Furthermore, the data analysis module is used to adjust the ventilation frequency to a corresponding value based on the time domain discreteness, 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 the ammonia concentration monitoring process based on the number ratio of the three-level points, including:

[0031] Calculate the difference between the proportion of the number of third-level points and the proportion of the first preset third-level points,

[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 the number 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 the monitoring of ammonia concentration 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 time based on the proportion of the number of primary points.

[0035] Furthermore, the data analysis module is used to adjust the feces cleaning frequency based on the number ratio of the secondary points, wherein:

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

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

[0038] If the distribution of the third-level points is concentrated, the data analysis module determines that the reason for the failure of the monitoring of ammonia concentration in the livestock breeding environment is that the feces are not cleaned in time, and adjusts the frequency of feces cleaning based on the proportion of the number of secondary points;

[0039] If the distribution of the third-level points is scattered, the data analysis module determines that the reason for the failure of the monitoring of 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 time based on the proportion of the number of primary points, wherein:

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

[0042] Compared with the prior art, the beneficial effect of the present invention lies in that a multi-point monitoring method is adopted in the present invention to obtain ammonia concentration data of multiple points, the points to be measured are marked according to the ammonia concentration of each point, the points to be measured with too high ammonia concentration are marked as third-level points, the number of each type of points is counted, and the ammonia concentration in the livestock breeding environment is comprehensively analyzed according to the proportion of the number of third-level points. When the proportion of the number of third-level points is high, the corresponding treatment method is determined in time, thereby reducing the ammonia concentration in time, 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 the present invention, when the ammonia concentration is between the first preset ammonia concentration and the second preset ammonia concentration, the type of the point to be measured is secondarily determined 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 easy to increase in a short time, the point to be measured is marked as a third-level point, thereby improving the control accuracy of each point to be measured and improving the analysis accuracy of the ammonia concentration in the breeding environment.

[0044] Furthermore, the present invention analyzes whether the distribution of ammonia generation sources in the breeding environment is uniform according to the time domain discreteness of the ammonia concentration at each test point, and then determines the treatment method for the breeding environment according to the time domain discreteness. When the time domain discreteness is small, it is determined that the distribution of ammonia generation sources is relatively uniform, and the ventilation batches are increased, thereby increasing the reduction rate of ammonia concentration and improving environmental safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a structural block diagram of the livestock breeding environment control system based on self-learning of the present invention;

[0046] Figure 2 A flow chart for determining the type of the point to be tested;

[0047] Figure 3 A flow chart for secondary determination of the type of the point to be measured;

[0048] Figure 4 A flow chart for preliminary analysis of whether the monitoring of ammonia concentration in livestock breeding environments is qualified. DETAILED DESCRIPTION

[0049] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0050] It should be pointed out that the data in this embodiment are obtained by comprehensive analysis and evaluation of the historical data of the system of the present invention in the six months before this determination and the corresponding historical determination results. It can be understood by those skilled in the art that the determination method of the system of the present invention for a single parameter mentioned above can be to select the value with the highest proportion as the preset standard parameter according to the data distribution, use weighted summation to use the obtained value as the preset standard parameter, substitute each historical data into a specific formula and use the value obtained by the formula as the preset standard parameter or other selection methods, as long as the system of the present invention can clearly define different specific situations in the single determination process through the obtained values.

[0051] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0052] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0053] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

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

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

[0056] A collection module, which includes sensors arranged at a number of points to be measured in the livestock breeding environment, for collecting ammonia concentrations at corresponding points;

[0057] A drawing module, connected to the acquisition module, for drawing an ammonia concentration-time curve based on the collected ammonia concentrations of each of the test points;

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

[0059] A data analysis module is respectively connected to the acquisition module, the drawing module and the marking module, and is used to preliminarily analyze whether the monitoring of ammonia concentration in the livestock breeding environment is qualified based on the proportion of the number of marked third-level points, and when it is preliminarily determined that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, a secondary determination is made on whether the monitoring is qualified based on the time domain discreteness of the ammonia concentration of each of the test points at the current time node, or a processing method for the ammonia concentration monitoring process is analyzed based on the proportion of the number of third-level points.

[0060] The present invention adopts a multi-point monitoring method to obtain ammonia concentration data of multiple points, marks the points to be measured according to the ammonia concentration of each point, marks the points to be measured with too high ammonia concentration as third-level points, counts the number of points of each type, and comprehensively analyzes the ammonia concentration in the livestock breeding environment according to the proportion of the number of third-level points. When the proportion of the number of third-level points is high, the corresponding treatment method is determined in time, thereby reducing the ammonia concentration in time, matching the breeding environment with the ammonia monitoring method, thereby effectively controlling the ammonia concentration in the livestock breeding environment and improving environmental safety.

[0061] See also Figure 2 As shown, it is a flow chart for determining the type of the point to be tested.

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

[0063] If the ammonia concentration is less than or equal to the first preset ammonia concentration, the marking module determines to mark the point to be measured 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 to perform a secondary determination on the type of the point to be measured based on the ammonia concentration-time curve of the point to be measured;

[0065] If the ammonia concentration is greater than the second preset ammonia concentration, the marking module determines to mark the point to be measured as a third-level point.

[0066] Specifically, in this embodiment, the first preset ammonia concentration and the second preset ammonia concentration are obtained in advance, and the highest ammonia concentration in several livestock breeding environments with qualified air quality is obtained to solve the average ammonia concentration. 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] See also Figure 3 As shown, it is a determination flow chart for secondary determination of the type of the point to be measured.

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

[0069] Calculate the slope of the ammonia concentration-time curve of the test point at the current time node,

[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 third-level 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 by pre-measurement, and the ammonia concentration change data in several livestock breeding environments with qualified air quality are obtained, and the ammonia concentration-time curves are drawn respectively, and the time interval from the last ventilation end time node to the current time node in the current ammonia concentration-time curve is determined. Based on the time interval, the corresponding time nodes in each curve are selected, the slope at each selected time node is determined, the mean slope is solved, and the preset slope is obtained.

[0073] In the present invention, when the ammonia concentration is between the first preset ammonia concentration and the second preset ammonia concentration, the type of the point to be measured is secondarily determined 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 easy to increase in a short time, the point to be measured is marked as a third-level point, thereby improving the control accuracy of each point to be measured and improving the analysis accuracy of the ammonia concentration in the breeding environment.

[0074] See also Figure 4 As shown, it is a flow chart 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 preliminarily analyze whether the monitoring of ammonia concentration in the livestock breeding environment is qualified based on the number ratio of the marked third-level points, including:

[0076] If the number ratio of the third-level points is greater than or equal to the first preset third-level number ratio, 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 number ratio of the third-level points;

[0077] If the proportion of the number of the third-level points is less than the first preset third-level proportion and greater than or equal to the second preset third-level proportion, the data analysis module preliminarily 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 discreteness of the ammonia concentration of each of the test points at the current time node;

[0078] If the proportion of the number of the third-level points is less than the second preset proportion of the third-level points, the data analysis module determines that the monitoring of the 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 make a secondary determination on whether the monitoring is qualified based on the time domain discreteness of the ammonia concentration of each of the test points at the current time node, including:

[0081] Calculate the variance of the ammonia concentration at each of the test points at the current time node to obtain the time domain discreteness.

[0082] If the time domain discreteness is greater than or equal to the preset time domain discreteness, 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 number ratio of the third-level points;

[0083] If the time domain discreteness is less than the preset time domain discreteness, 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 a corresponding value.

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

[0085] In the present invention, whether the distribution of ammonia generation sources in the breeding environment is uniform is analyzed according to the time domain discreteness of the ammonia concentration at each test point, and then the treatment method for the breeding environment is determined according to the time domain discreteness. When the time domain discreteness is small, it is determined that the distribution of ammonia generation sources is relatively uniform, and the ventilation batches are increased, thereby increasing the reduction rate of ammonia concentration 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 discreteness, 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 discreteness is less than or equal to the first preset time domain discreteness, the first ventilation frequency is increased, and the first ventilation frequency is 0.1 times the initial ventilation frequency;

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

[0092] If the time domain discreteness is greater than the second preset time domain discreteness, the third ventilation frequency is increased, and the third ventilation frequency is 0.25 times the initial ventilation frequency;

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

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

[0095] Calculate the difference between the proportion of the number of third-level points and the proportion of the first preset third-level points,

[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 the number 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 the monitoring of ammonia concentration 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 time based on the proportion of the number 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 feces cleaning frequency based on the number ratio of the secondary points, wherein:

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

[0102] In this embodiment, optionally,

[0103] Compare the proportion of the number of secondary points with the first preset proportion of the number of secondary points and the second preset proportion of the number of secondary points.

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

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

[0106] If the proportion of the number of secondary points is greater than the second preset proportion of the number of secondary points, the third cleaning frequency is increased, and the third cleaning frequency is 0.2 times the initial cleaning frequency;

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

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

[0109] If the distribution of the third-level points is concentrated, the data analysis module determines that the reason for the failure of the monitoring of ammonia concentration in the livestock breeding environment is that the feces are not cleaned in time, and adjusts the frequency of feces cleaning based on the proportion of the number of secondary points;

[0110] If the distribution of the third-level points is scattered, the data analysis module determines that the reason for the failure of the monitoring of 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 time based on the proportion of the number of primary points, wherein:

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

[0113] In this embodiment, optionally,

[0114] Compare the first-level point quantity ratio with the first preset quantity ratio and the second preset quantity ratio.

[0115] If the proportion of the number of first-level points is less than or equal to the first preset proportion, the first ventilation time is increased, and the first ventilation time is 0.25 times the initial ventilation time;

[0116] If the proportion of the number of first-level points is greater than the first preset proportion and less than or equal to the second preset proportion, the second ventilation time is increased, and the second ventilation time is 0.2 times the initial ventilation time;

[0117] If the proportion of the first-level points is greater than the proportion of the second preset number, the third ventilation time is increased, and the third ventilation time is 0.1 times the initial ventilation time;

[0118] Among them, the first preset quantity accounts for 1.1 times the first preset three-level quantity, and the second preset quantity accounts for 1.2 times the first preset three-level quantity.

[0119] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle 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 fall within the protection scope of the present invention.

[0120] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A livestock breeding environment control system based on self-learning, characterized in that: include: A collection module, which includes sensors arranged at a number of points to be measured in the livestock breeding environment, for collecting ammonia concentrations at corresponding points; A drawing module, connected to the acquisition module, for drawing an ammonia concentration-time curve based on the collected ammonia concentrations of each of the test points; A marking module, which is connected to the acquisition module and the drawing module respectively, and is used to mark each of the points to be measured based on the measured ammonia concentration, and count the number of each type of marked points; A data analysis module is respectively connected to the acquisition module, the drawing module and the marking module, and is used to preliminarily analyze whether the monitoring of ammonia concentration in the livestock breeding environment is qualified based on the proportion of the number of marked third-level points, and when it is preliminarily determined that the monitoring of ammonia concentration in the livestock breeding environment is unqualified, a secondary determination is made on whether the monitoring is qualified based on the time domain discreteness of the ammonia concentration of each of the test points at the current time node, or a processing method for the ammonia concentration monitoring process is analyzed based on the proportion of the number of third-level points.

2. The livestock breeding environment control system based on self-learning according to claim 1 is characterized in that: The marking module is used to mark the point to be measured based on the ammonia concentration of the single point to be measured 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 point to be measured 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 to perform a secondary determination on the type of the point to be measured based on the ammonia concentration-time curve of the point to be measured; If the ammonia concentration is greater than the second preset ammonia concentration, the marking module determines to mark the point to be measured as a third-level point.

3. The livestock breeding environment control system based on self-learning according to claim 2 is characterized in that: The marking module is used to perform a secondary determination on the type of the point to be measured based on the ammonia concentration-time curve of the point to be measured, including: Calculate the slope of the ammonia concentration-time curve of the test point at the current time node, 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 third-level 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.

4. The livestock breeding environment control system based on self-learning according to claim 1 is characterized in that: The data analysis module is used to preliminarily analyze whether the monitoring of ammonia concentration in the livestock breeding environment is qualified based on the number ratio of the marked third-level points, including: If the number ratio of the third-level points is greater than or equal to the first preset third-level number ratio, 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 number ratio of the third-level points; If the proportion of the number of the third-level points is less than the first preset third-level proportion and greater than or equal to the second preset third-level proportion, the data analysis module preliminarily 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 discreteness of the ammonia concentration of each of the test points at the current time node; If the proportion of the number of the third-level points is less than the second preset proportion of the third-level points, the data analysis module determines that the monitoring of the ammonia concentration in the livestock breeding environment is qualified.

5. The livestock breeding environment control system based on self-learning according to claim 4 is characterized in that: The data analysis module is used to perform a secondary determination on whether the monitoring is qualified based on the time domain dispersion of the ammonia concentration of each of the test points at the current time node, including: Calculate the variance of the ammonia concentration at each of the test points at the current time node to obtain the time domain discreteness. If the time domain discreteness is greater than or equal to the preset time domain discreteness, 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 number ratio of the third-level points; If the time domain discreteness is less than the preset time domain discreteness, 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 a corresponding value.

6. The livestock breeding environment control system based on self-learning according to claim 5, characterized in that: The data analysis module is used to adjust the ventilation frequency to a corresponding value based on the time domain discreteness, wherein: The increase in ventilation frequency is positively correlated with the time domain dispersion.

7. The livestock breeding environment control system based on self-learning according to claim 5, characterized in that: The data analysis module is used to analyze the processing method for the ammonia concentration monitoring process based on the number ratio of the three-level points, including: Calculate the difference between the proportion of the number of third-level points and the proportion of the first preset third-level points, 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 the number 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 the monitoring of ammonia concentration 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 time based on the proportion of the number of primary points.

8. The livestock breeding environment control system based on self-learning according to claim 7 is characterized in that: The data analysis module is used to adjust the feces cleaning frequency based on the proportion of the number of secondary points, wherein: The increase in the frequency of feces cleaning is positively correlated with the proportion of the number of secondary points.

9. The livestock breeding environment control system based on self-learning according to claim 7, characterized in that: The data analysis module is used to analyze the reasons for the failure of monitoring ammonia concentration in the livestock breeding environment based on the distribution of the three-level points, including: If the distribution of the third-level points is concentrated, the data analysis module determines that the reason for the failure of the monitoring of ammonia concentration in the livestock breeding environment is that the feces are not cleaned in time, and adjusts the frequency of feces cleaning based on the proportion of the number of secondary points; If the distribution of the third-level points is scattered, the data analysis module determines that the reason for the failure of the monitoring of 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.

10. The livestock breeding environment control system based on self-learning according to claim 7, characterized in that: The data analysis module is used to adjust the ventilation time based on the proportion of the number of primary points, wherein: The increase in ventilation time is negatively correlated with the proportion of primary points.

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