Breeding duck farm environment management optimization method and system based on AI analysis

Abstract

The invention discloses a breeding duck farm environment management optimization method and system based on AI analysis, and relates to the technical field of breeding duck farm management, and the method comprises the steps: obtaining a farm design drawing of a breeding duck farm and a ventilated peripheral region; acquiring an environment monitoring point and a wind speed monitoring point in the breeding duck farm by using a wind direction positioning method, and acquiring a wind speed standard in the farm; acquiring a resident detection point and a change detection point; managing the breeding duck farm environment based on AI; the method is used for solving the problems that in an existing breeding duck farm environment management optimization method, data acquisition point positions are conventional and fixed, the installation position of a sensor cannot be determined based on the environment condition in a breeding duck farm, and the installation position of the sensor cannot be changed based on real-time environment change, so that acquired environment data are inaccurate, and the data are not accurate. And the problem of omission of environment management optimization is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of breeding duck farm management, and specifically to an optimization method and system for the environment management of a breeding duck farm based on AI analysis. Background Art

[0002] A breeding duck farm refers to a place specifically used for raising and managing breeding ducks, and its main purpose is to breed and cultivate healthy ducklings; the management of a breeding duck farm mainly includes: feeding management, disease prevention and control, selection and ratio of breeding ducks, and environment management. Among them, environment management mainly includes temperature control, humidity control, and ventilation control; the main measures for optimizing the environment management of a breeding duck farm include reasonable control of temperature and humidity, ventilation design, disinfection, deodorization, humidification, and feed cost management.

[0003] Existing methods for optimizing the environment management of a breeding duck farm usually analyze the growth state information of the breeding ducks in the farm, obtain the environmental data in the breeding duck farm by installing sensors, and combine and analyze the growth state information of the breeding ducks with the environmental data in the breeding duck farm to obtain environmental impact factors that have a relatively high impact on the growth state of the breeding ducks, and then optimize the environment of the breeding duck farm. Although this improved method can reduce the impact of the environment on the growth process of the breeding ducks, in the collection of environmental data, the data collection points are relatively conventional and fixed, and it is impossible to determine the installation position of the sensors based on the environmental conditions in the breeding duck farm, and at the same time, it is impossible to change the installation position of the sensors based on real-time environmental changes, resulting in inaccurate environmental data and omissions in environmental management optimization. For example, in the patent application with the publication number CN119323290A, an intelligent duck farm environment management optimization method and system are disclosed. This solution filters high-weight environmental impact factors based on growth attributes, sets key environmental impact factors for multiple growth scenarios based on high-weight environmental impact factors, collects environmental impact factors for multiple growth scenarios, and configures a matching environmental log for the healthy growth of breeding ducks to perform semantic processing. Other improvements in the optimization of the environment management of a breeding duck farm are usually improvements in the equipment in the breeding duck farm, and still cannot solve the problem that in the collection of environmental data, the data collection points are relatively conventional and fixed, and it is impossible to determine the installation position of the sensors based on the environmental conditions in the breeding duck farm, and at the same time, it is impossible to change the installation position of the sensors based on real-time environmental changes, resulting in inaccurate environmental data and omissions in environmental management optimization. In view of this, it is necessary to improve the existing methods for optimizing the environment management of a breeding duck farm. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems in the prior art to some extent. By proposing an optimization method and system for the environmental management of a breeding duck farm based on AI analysis, it is used to solve the problems in the existing optimization methods for the environmental management of breeding duck farms. In the collection of environmental data, the data collection points are relatively conventional and fixed, and it is impossible to determine the installation positions of sensors based on the environmental conditions in the breeding duck farm. At the same time, it is impossible to change the installation positions of sensors based on real-time environmental changes, resulting in inaccurate environmental data and omissions in environmental management optimization.

[0005] To achieve the above object, on the first aspect, the present application provides an optimization method for the environmental management of a breeding duck farm based on AI analysis, including the following steps: Obtain the site design drawing of the breeding duck farm, and based on the site design drawing, obtain the ventilable peripheral area of the breeding duck farm; Place wind speed sensors in the ventilable peripheral area, and use the wind direction positioning method based on the sensing data of the wind speed sensors to obtain the environmental monitoring points and wind speed monitoring points in the breeding duck farm; Screen the wind speed monitoring points based on the wind speed sensors, and obtain the in-farm wind speed standard based on the screening results, where the in-farm wind speed standard includes the in-farm direction and the in-farm wind speed; Screen the environmental monitoring points based on the in-farm wind speed standard, and obtain the permanent detection points and variable detection points based on the screening results; Import the real-time sensing data of the wind speed sensors and the wind direction positioning method into the AI, obtain the environmental monitoring points and wind speed monitoring points in real time based on the AI, and update the in-farm wind speed standard, permanent detection points, and variable detection points; Manage the environment of the breeding duck farm based on the latest permanent detection points and variable detection points.

[0006] Further, obtaining the site design drawing of the breeding duck farm and obtaining the ventilable peripheral area of the breeding duck farm based on the site design drawing includes: Obtain the site design drawing of the breeding duck farm, and mark the area where the duck house is located in the site design drawing as the duck house area; Mark the area where air circulation is allowed in the duck house area as the ventilable area, and mark the closed figure corresponding to the boundary of the duck house in the site design drawing as the duck house edge area; Mark the area where the ventilable area coincides with the duck house edge area as the ventilable peripheral area; Mark all independent areas in the ventilable peripheral area as ventilable sub-areas KZ 1 to ventilable sub-areas KZ v ; For any one ventilable sub-area KZ b , mark the points where the ventilable sub-area KZ b coincides with the duck house edge area as boundary coincidence point A and boundary coincidence point B respectively, where b is a positive integer less than or equal to v and greater than or equal to 1; Mark the distance between boundary coincidence point A and boundary coincidence point B as the sub-area length.

[0007] Further, placing the wind speed sensors in the ventilable peripheral area includes: When the length of the sub-region is greater than L, the value obtained by dividing the length of the sub-region by L and rounding up is denoted as j. j points are evenly obtained on the line connecting the boundary coincidence point A and the boundary coincidence point B, and all are denoted as wind speed placement points. When the length of the sub-region is less than or equal to L, the midpoint of the line connecting the boundary coincidence point A and the boundary coincidence point B is denoted as the wind speed placement point, where L is the minimum installation interval of the wind speed sensor. Obtain the wind speed placement points of all ventilable sub-regions KZ, place wind speed sensors at the wind speed placement points, and denote them as off-site sensors.

[0008] Further, the wind direction positioning method includes: Denote the sensing data of all off-site sensors as wind speed sensing data. Establish a plane rectangular coordinate system with the unit of both the X-axis and the Y-axis being m, and denote it as the ventilation analysis coordinate system. Place the duck house area proportionally in the ventilation analysis coordinate system, and mark the positions of the wind speed placement points.

[0009] Further, the wind direction positioning method also includes: In the ventilation analysis coordinate system: For any wind speed sensing data obtained, based on the position of the off-site sensor, mark the wind speed and wind direction at the wind speed placement point. Among them, based on the wind direction, draw a ray at the wind speed placement point, and denote it as the ventilation ray. The direction of the ventilation ray is the orientation of the wind direction. Obtain the ventilation rays corresponding to the wind speed sensing data. Denote the intersection point of all ventilation rays within the duck house area as the wind speed monitoring point, and denote the number of wind speed monitoring points as k. Denote the independent areas divided by all ventilation rays within the duck house area as regular areas, and denote the top k regular areas arranged in descending order of area among all regular areas as regular detection areas. Obtain the center of the minimum circumscribed circle of all regular detection areas, and denote it as the environmental monitoring point.

[0010] Further, screening the wind speed monitoring points based on the wind speed sensors, and obtaining the in-field wind speed standard based on the screening results includes: Place wind speed sensors at all wind speed monitoring points, and denote them as in-field sensors. Based on the sensing data of the in-field sensors, mark the wind speed and wind direction at the wind speed monitoring points. For any wind speed monitoring point: When the wind direction marked at the wind speed monitoring point is the same as the direction of the ventilation ray where the wind speed monitoring point is located, denote the wind speed monitoring point as a co-directional monitoring point. When the wind direction marked at the wind speed monitoring point is different from the direction of the ventilation ray where the wind speed monitoring point is located, denote the wind speed monitoring point as a counter-directional monitoring point. When the number of in - direction monitoring points is greater than that of cross - direction monitoring points, use the in - direction analysis algorithm to obtain the in - direction wind difference of each in - direction monitoring point, and record the marked wind speed and wind direction of the in - direction monitoring point corresponding to the maximum in - direction wind difference as the in - field wind speed and in - field wind direction respectively. Among them, the in - direction analysis algorithm is: Z = Z 0 -Z 1 , where Z is the in - direction wind difference, Z 0 is the marked wind speed of the in - direction monitoring point, and Z 1 is the marked wind speed of the wind speed placement point in the ventilation ray where the in - direction monitoring point is located; When the number of in - direction monitoring points is less than or equal to that of cross - direction monitoring points, use the cross - direction analysis algorithm to obtain the cross - direction wind difference of each cross - direction monitoring point, and record the marked wind speed and wind direction of the cross - direction monitoring point corresponding to the maximum cross - direction wind difference as the in - field wind speed and in - field wind direction respectively. Among them, the cross - direction analysis algorithm is: D = d - β, where D is the cross - direction wind difference, β is the marked wind speed of the wind speed placement point in the ventilation ray where the cross - direction monitoring point is located, and d is the component of the marked wind speed of the cross - direction monitoring point in the direction of the ventilation ray where the cross - direction monitoring point is located.

[0011] Further, screen the environmental monitoring points based on the in - field wind speed standard, and obtain the permanent detection points and variable detection points based on the screening results, including: Use wind speed sensors to obtain the wind direction of each environmental monitoring point respectively; for any environmental monitoring point, when the included angle between the wind direction of the environmental monitoring point and the in - field direction is less than 90°, record the environmental monitoring point as a variable detection point; When the included angle between the wind direction of the environmental monitoring point and the in - field direction is equal to 90°, record the environmental monitoring point as a permanent detection point.

[0012] Further, manage the breeding duck farm environment based on the latest permanent detection points and variable detection points, including: Import the real - time sensing data of the off - field sensor and the wind direction positioning method into the AI; based on the AI data processing, update the environmental monitoring points and wind speed monitoring points in the duck house area in real - time, and update the in - field wind speed standard and variable detection points based on the latest obtained environmental monitoring points and wind speed monitoring points, where the positions of the permanent detection points remain unchanged.

[0013] Further, managing the breeding duck farm environment based on the latest permanent detection points and variable detection points also includes: Place environmental sensors at the permanent detection points and the latest variable detection points, and adjust the ventilable area of the duck house based on the sensing data of the environmental sensors until the data of all environmental sensors are standard data, where the standard data is the environmental data that allows the breeding ducks to grow normally.

[0014] In a second aspect, the present application also provides an optimization system for the environmental management of a breeding duck farm based on AI analysis, including a wind speed environmental detection module, an environmental analysis fixed-point module, and an AI management optimization module; The wind speed environmental detection module is used to obtain the site design drawing of the breeding duck farm and obtain the ventilable peripheral area of the breeding duck farm based on the site design drawing; place wind speed sensors in the ventilable peripheral area, and use the wind direction positioning method based on the sensing data of the wind speed sensors to obtain the environmental monitoring points and wind speed monitoring points in the breeding duck farm; The environmental analysis fixed-point module is used to screen the wind speed monitoring points based on the wind speed sensors, and obtain the in-farm wind speed standard based on the screening results, where the in-farm wind speed standard includes the in-farm direction and the in-farm wind speed; screen the environmental monitoring points based on the in-farm wind speed standard, and obtain the permanent detection points and variable detection points based on the screening results; The AI management optimization module is used to import the real-time sensing data of the wind speed sensors and the wind direction positioning method into the AI, obtain the environmental monitoring points and wind speed monitoring points in real time based on the AI, and update the in-farm wind speed standard, permanent detection points, and variable detection points; manage the environment of the breeding duck farm based on the latest permanent detection points and variable detection points.

[0015] Advantages of the present invention: The present application first obtains the site design drawing of the breeding duck farm and obtains the ventilable peripheral area; places wind speed sensors in the ventilable peripheral area, and uses the wind direction positioning method based on the sensing data of the wind speed sensors to obtain the environmental monitoring points and wind speed monitoring points in the breeding duck farm. The advantage of this is that by placing wind speed sensors and obtaining environmental monitoring points and wind speed monitoring points, it is possible to obtain monitorable points in areas with a relatively large air circulation rate, i.e., a relatively fast wind speed, and areas with a relatively small air circulation rate, i.e., a relatively slow wind speed, in the duck houses of the breeding duck farm, which helps to collect environmental data in the duck houses during subsequent analysis and prevent the problem of inaccurate environmental data obtained due to the inability to determine the installation position of the sensors based on the environmental conditions in the breeding duck farm; This application also screens the wind speed monitoring points based on a wind speed sensor, and obtains the in-field wind speed standard based on the screening results; screens the environmental monitoring points based on the in-field wind speed standard, and obtains the permanent detection points and variable detection points based on the screening results; imports the real-time sensing data of the wind speed sensor and the wind direction positioning method into the AI, and obtains the environmental monitoring points and wind speed monitoring points in real time based on the AI, and updates the in-field wind speed standard, permanent detection points and variable detection points; finally, manages the environment of the breeding duck farm based on the latest permanent detection points and variable detection points. The advantage of this is that by obtaining the in-field wind speed standard, it is possible to obtain the air circulation in the duck house of the breeding duck farm, that is, the positions with faster wind speed; and based on the in-field wind speed standard to obtain the regular detection points and variable detection points, it is possible to distinguish the points in the duck house that are greatly affected by air circulation and the points that are less affected by air circulation, so as to flexibly change the installation position of the sensor in the subsequent environmental data collection to ensure more comprehensive collection of environmental data in the duck house. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a schematic block diagram of the system of the present invention; Figure 2 is a flowchart of the steps of the method of the present invention; Figure 3 is a schematic diagram for obtaining the wind speed placement points of the present invention; Figure 4 is a schematic diagram of the positions of the wind speed placement points and the different-direction monitoring points of the present invention; Figure 5 is a schematic diagram of the structure of the electronic device of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] Example 1, please refer to Figure 1 As shown, this application provides an optimized system for breeding duck farm environment management based on AI analysis, including a wind speed environment detection module, an environmental analysis and fixed-point module, and an AI management and optimization module; The wind speed environment detection module is used to obtain the site design drawing of the breeding duck farm, and obtain the ventilable peripheral area of the breeding duck farm based on the site design drawing; place wind speed sensors in the ventilable peripheral area, and use the wind direction positioning method based on the sensing data of the wind speed sensors to obtain the environmental monitoring points and wind speed monitoring points in the breeding duck farm; The wind speed environment detection module includes a duck farm environment analysis unit, and the duck farm environment analysis unit is configured with a duck farm environment analysis strategy. The duck farm environment analysis strategy includes: Obtain the site design drawing of the breeding duck farm, and mark the area where the duck house is located in the site design drawing as the duck house area; mark the area where air circulation is allowed in the duck house area as the ventilable area, and mark the closed figure corresponding to the boundary of the duck house in the site design drawing as the duck house edge area; mark the area where the ventilable area coincides with the duck house edge area as the ventilable peripheral area; In the specific implementation process, when the ventilable area in the boundary of the duck house is marked in the site design drawing of the breeding duck farm, the marked ventilable area can be directly obtained and marked as the ventilable peripheral area; by obtaining the ventilable peripheral area, it is helpful to obtain the installation positions of off-site sensors in the subsequent analysis, so as to obtain the data corresponding to the ventilation state of the duck house, and then optimize the environmental management of the duck house in the breeding duck farm; Mark all independent areas in the ventilable peripheral area as ventilable sub-areas KZ 1 to ventilable sub-areas KZ v ; for any ventilable sub-area KZ b , mark the points where the ventilable sub-area KZ b coincides with the duck house edge area as boundary coincidence point A and boundary coincidence point B respectively, where b is a positive integer less than or equal to v and greater than or equal to 1; mark the distance between boundary coincidence point A and boundary coincidence point B as the sub-area length; When the sub-area length is greater than L, mark the value obtained by dividing the sub-area length by L and rounding up as j, and uniformly obtain j points on the line connecting boundary coincidence point A and boundary coincidence point B, and all are marked as wind speed placement points; when the sub-area length is less than or equal to L, mark the midpoint of the line connecting boundary coincidence point A and boundary coincidence point B as the wind speed placement point, where L is the minimum installation interval of the wind speed sensor; In the specific implementation process, for example, in a data analysis, the obtained boundary coincidence point A and boundary coincidence point B are respectively as Figure 3As shown by AA1 and BB1 in [description], the length of the sub-region in DD1 is less than L, indicating that only one wind speed sensor can be placed between the boundary coincidence point A and the boundary coincidence point B. Therefore, a wind speed sensor can be placed at point OO1, which is the midpoint of the line connecting the boundary coincidence point A and the boundary coincidence point B, to detect the wind speed data at this location. In actual applications, the wind speed placement point can be obtained according to the allowable installation positions of the wind speed sensors. The analysis in this embodiment is only to determine the number of wind speed placement points in the line connecting the boundary coincidence point A and the boundary coincidence point B; in addition, the length of the sub-region in DD2 is greater than L, indicating that the distance between the boundary coincidence point A and the boundary coincidence point B is relatively large, and multiple wind speed sensors can be placed. Given that L is obtained as 5 meters through data acquisition and the length of the sub-region in DD2 is 8 meters, two wind speed sensors can be placed in the line connecting the boundary coincidence point A and the boundary coincidence point B. Through analysis, the wind speed placement points are OO2 and OO3 respectively.

[0019] Obtain the wind speed placement points of all ventilable sub-regions KZ, place wind speed sensors at the wind speed placement points, and denote them as off-site sensors; The wind direction positioning method includes: recording the sensing data of all off-site sensors as wind speed sensing data; establishing a plane rectangular coordinate system with the units of both the X-axis and the Y-axis being m, and denoting it as the ventilation analysis coordinate system; placing the duck house area proportionally in the ventilation analysis coordinate system and marking the positions of the wind speed placement points; In the ventilation analysis coordinate system: for any obtained wind speed sensing data, mark the wind speed and wind direction at the wind speed placement points based on the positions of the off-site sensors. Among them, a ray is drawn at the wind speed placement point based on the wind direction, and it is denoted as the ventilation ray. The direction of the ventilation ray is the orientation of the wind direction; Obtain the ventilation rays corresponding to the wind speed sensing data; denote the intersection points of all ventilation rays in the duck house area as wind speed monitoring points, and denote the number of wind speed monitoring points as k; denote the independent areas divided by all ventilation rays in the duck house area as regular areas, and denote the first k regular areas arranged in descending order of area among all regular areas as regular detection areas; obtain the centers of the minimum circumscribed circles of all regular detection areas, and denote them as environmental monitoring points; In the specific implementation process, in this embodiment, the wind speed monitoring points are the points affected by winds from multiple directions, that is, the points affected more by ventilation; the environmental monitoring points are the positions farther from the air circulation positions, that is, the points affected less by ventilation. Therefore, by obtaining the wind speed monitoring points and environmental monitoring points, environmental analysis can be carried out separately on the points with greater air circulation and the points with less air circulation in the duck house during subsequent analysis to ensure the comprehensiveness and accuracy of environmental analysis and environmental management optimization.

[0020] The environmental analysis fixed-point module is used to screen wind speed monitoring points based on a wind speed sensor, and obtain the in-site wind speed standard based on the screening results. The in-site wind speed standard includes the in-site direction and the in-site wind speed. The environmental monitoring points are screened based on the in-site wind speed standard, and the resident detection points and the variable detection points are obtained based on the screening results. The environmental analysis fixed-point module includes an environmental analysis fixed-point unit, and the environmental analysis fixed-point unit is configured with an environmental analysis fixed-point strategy. The environmental analysis fixed-point strategy includes: Place wind speed sensors at all wind speed monitoring points and record them as in-site sensors. Mark the wind speed and wind direction at the wind speed monitoring points based on the sensing data of the in-site sensors. For any wind speed monitoring point: when the marked wind direction at the wind speed monitoring point is the same as the direction of the ventilation ray where the wind speed monitoring point is located, the wind speed monitoring point is recorded as a co-directional monitoring point; when the marked wind direction at the wind speed monitoring point is different from the direction of the ventilation ray where the wind speed monitoring point is located, the wind speed monitoring point is recorded as a counter-directional monitoring point. When the number of co-directional monitoring points is greater than the number of counter-directional monitoring points, use the co-directional analysis algorithm to obtain the co-directional wind difference of each co-directional monitoring point, and record the marked wind speed and wind direction of the co-directional monitoring point corresponding to the largest co-directional wind difference as the in-site wind speed and the in-site wind direction respectively. The co-directional analysis algorithm is: Z = Z 0 -Z 1 , where Z is the co-directional wind difference, Z 0 is the marked wind speed of the co-directional monitoring point, and Z 1 is the marked wind speed of the wind speed placement point in the ventilation ray where the co-directional monitoring point is located. In the specific implementation process, for example, in a data analysis, the marked wind speed of the co-directional monitoring point is 5 m / s, and the marked wind speed of the wind speed placement point in the ventilation ray where the co-directional monitoring point is located is 3 m / s. Then, through calculation, the co-directional wind difference is 2 m / s. By obtaining the co-directional wind difference, the point with a faster wind speed change among the co-directional monitoring points can be obtained, that is, the point that can represent a larger air circulation rate in the duck house, which helps to analyze whether the environmental monitoring points are affected by air circulation during subsequent analysis, and then screen the environmental monitoring points. When the number of co-directional monitoring points is less than or equal to the number of counter-directional monitoring points, use the counter-directional analysis algorithm to obtain the counter-directional wind difference of each counter-directional monitoring point, and record the marked wind speed and wind direction of the counter-directional monitoring point corresponding to the largest counter-directional wind difference as the in-site wind speed and the in-site wind direction respectively. The counter-directional analysis algorithm is: D = d - β, where D is the counter-directional wind difference, β is the marked wind speed of the wind speed placement point in the ventilation ray where the counter-directional monitoring point is located, and d is the component of the marked wind speed of the counter-directional monitoring point in the direction of the ventilation ray where the counter-directional monitoring point is located. In the specific implementation process, for example, in a data analysis, the marked wind speed of the wind speed placement point in the ventilation ray where the counter-directional monitoring point is located is 3 m / s, and the obtained ventilation ray is asFigure 4 As shown in the figure, among them, the point where △ is located is the wind speed placement point, the point where ○ is located is the crosswind monitoring point, and at the same time, the direction indicated by the arrow T is the wind direction of the crosswind monitoring point. The wind speed of the crosswind monitoring point is 5 m / s, and the included angle α is 30°. Then, through analysis, it can be obtained that the component of the marked wind speed of the crosswind monitoring point in the direction of the ventilation ray where the crosswind monitoring point is located is 4 m / s. Then, through calculation, the crosswind difference can be obtained as 1. By calculating the crosswind difference, the wind speed difference in the same direction when the wind speed of the crosswind monitoring point is affected by the wind speed of the wind speed placement point can be obtained. The larger the crosswind difference, the greater the influence of the wind speed of the wind speed placement point on the wind speed of the crosswind monitoring point. Use wind speed sensors to obtain the wind direction of each environmental monitoring point respectively; for any environmental monitoring point, when the included angle between the wind direction of the environmental monitoring point and the in-field direction is less than 90°, the environmental monitoring point is recorded as a variable detection point. When the included angle between the wind direction of the environmental monitoring point and the in-field direction is equal to 90°, the environmental monitoring point is recorded as a permanent detection point. In the specific implementation process, by screening the environmental monitoring points to obtain variable detection points and permanent detection points, it is possible to respectively obtain the points in the duck house that are greatly affected by air circulation and far from the air circulation position, and the points that are less affected by air circulation and far from the air circulation position. In subsequent data acquisition, under the condition of reducing the interference of air circulation on the environment in the duck house, data can be collected separately for the positions in the duck house where the air is greatly affected by the outside world and the positions where the air is less affected by the outside world, so as to ensure more comprehensive collection of environmental data in the duck house.

[0021] The AI management optimization module is used to import the real-time sensing data of the wind speed sensor and the wind direction positioning method into the AI, and based on the AI, obtain the environmental monitoring points and wind speed monitoring points in real time, and update the in-field wind speed standard, permanent detection points and variable detection points; manage the environment of the breeding duck farm based on the latest permanent detection points and variable detection points. The AI management optimization module includes a duck farm management optimization unit, and the duck farm management optimization unit is configured with a duck farm management optimization strategy, and the duck farm management optimization strategy includes: Import the real-time sensing data of the off-site sensor and the wind direction positioning method into the AI; based on the AI data processing, update the environmental monitoring points and wind speed monitoring points in the duck house area in real time, and update the in-field wind speed standard and variable detection points based on the latest obtained environmental monitoring points and wind speed monitoring points, where the position of the permanent detection point remains unchanged. In the specific implementation process, because the permanent detection point is less affected by air circulation and far from the air circulation position, when the variable detection point is updated, the permanent detection point is less affected, so the position of the permanent detection point can be not changed. Place environmental sensors at the permanent detection points and the latest change detection points, and adjust the ventilable area of the duck house based on the sensing data of the environmental sensors until the data of all environmental sensors are standard data, where the standard data are environmental data that allow the breeding ducks to grow normally.

[0022] Example 2, please refer to Figure 2 As shown, the present application also provides an optimization method for the environmental management of a breeding duck farm based on AI analysis, including the following steps: Step S1, obtain the site design drawing of the breeding duck farm, and obtain the ventilable peripheral area of the breeding duck farm based on the site design drawing; place wind speed sensors in the ventilable peripheral area, and use the wind direction positioning method to obtain the environmental monitoring points and wind speed monitoring points in the breeding duck farm based on the sensing data of the wind speed sensors; Step S1 includes: Step S101, obtain the site design drawing of the breeding duck farm, and mark the area where the duck house is located in the site design drawing as the duck house area; mark the area where air circulation is allowed in the duck house area as the ventilable area, and mark the closed figure corresponding to the boundary of the duck house in the site design drawing as the duck house edge area; mark the area where the ventilable area coincides with the duck house edge area as the ventilable peripheral area; Step S102, mark all independent areas in the ventilable peripheral area as ventilable sub-areas KZ 1 to ventilable sub-areas KZ v ; for any ventilable sub-area KZ b , mark the points where the ventilable sub-area KZ b coincides with the duck house edge area as boundary coincidence point A and boundary coincidence point B respectively, where b is a positive integer less than or equal to v and greater than or equal to 1; mark the distance between boundary coincidence point A and boundary coincidence point B as the sub-area length; Step S103, when the sub-area length is greater than L, mark the value obtained by dividing the sub-area length by L and rounding up as j, and evenly obtain j points on the line connecting boundary coincidence point A and boundary coincidence point B, and mark them all as wind speed placement points; when the sub-area length is less than or equal to L, mark the midpoint of the line connecting boundary coincidence point A and boundary coincidence point B as the wind speed placement point, where L is the minimum installation interval of the wind speed sensor; Step S104, obtain the wind speed placement points of all ventilable sub-areas KZ, place wind speed sensors at the wind speed placement points, and mark them as off-site sensors; Step S105, the wind direction positioning method includes: Step S1051, mark the sensing data of all off-site sensors as wind speed sensing data; establish a plane rectangular coordinate system with the unit of both the X-axis and the Y-axis being m, and mark it as the ventilation analysis coordinate system; place the duck house area in the ventilation analysis coordinate system in equal proportion, and mark the positions of the wind speed placement points; Step S1052, within the ventilation analysis coordinate system: For any acquired wind speed sensing data, mark the wind speed and wind direction at the wind speed placement point based on the position of the off-site sensor. Among them, draw a ray at the wind speed placement point based on the wind direction and denote it as the ventilation ray, and the direction of the ventilation ray is the orientation of the wind direction; Step S1053, obtain the ventilation rays corresponding to the wind speed sensing data; Denote the intersection point of all ventilation rays within the duck house area as the wind speed monitoring point, and denote the number of wind speed monitoring points as k; Denote the independent areas divided by all ventilation rays within the duck house area as the regular areas, and denote the top k regular areas arranged in descending order of area among all regular areas as the regular detection areas; Obtain the center of the minimum circumscribed circle of all regular detection areas and denote it as the environmental monitoring point.

[0023] Step S2, screen the wind speed monitoring points based on the wind speed sensors, and obtain the in-field wind speed standard based on the screening results, where the in-field wind speed standard includes the in-field direction and the in-field wind speed; Screen the environmental monitoring points based on the in-field wind speed standard, and obtain the permanent detection points and the variable detection points based on the screening results; Step S2 includes: Step S201, place wind speed sensors at all wind speed monitoring points and denote them as in-field sensors; Mark the wind speed and wind direction at the wind speed monitoring points based on the sensing data of the in-field sensors; For any wind speed monitoring point: When the marked wind direction at the wind speed monitoring point is the same as the direction of the ventilation ray where the wind speed monitoring point is located, denote the wind speed monitoring point as the co-directional monitoring point; When the marked wind direction at the wind speed monitoring point is different from the direction of the ventilation ray where the wind speed monitoring point is located, denote the wind speed monitoring point as the non-co-directional monitoring point; Step S202, when the number of co-directional monitoring points is greater than the number of non-co-directional monitoring points, use the co-directional analysis algorithm to obtain the co-directional wind difference of each co-directional monitoring point, and denote the marked wind speed and wind direction of the co-directional monitoring point corresponding to the maximum co-directional wind difference as the in-field wind speed and the in-field wind direction respectively, where the co-directional analysis algorithm is: Z = Z 0 -Z 1 , Z is the co-directional wind difference, Z 0 is the marked wind speed of the co-directional monitoring point, Z 1 is the marked wind speed of the wind speed placement point in the ventilation ray where the co-directional monitoring point is located; Step S203, when the number of co-directional monitoring points is less than or equal to the number of non-co-directional monitoring points, use the non-co-directional analysis algorithm to obtain the non-co-directional wind difference of each non-co-directional monitoring point, and denote the marked wind speed and wind direction of the non-co-directional monitoring point corresponding to the maximum non-co-directional wind difference as the in-field wind speed and the in-field wind direction respectively, where the non-co-directional analysis algorithm is: D = d - β, D is the non-co-directional wind difference, β is the marked wind speed of the wind speed placement point in the ventilation ray where the non-co-directional monitoring point is located, and d is the component of the marked wind speed of the non-co-directional monitoring point in the direction of the ventilation ray where the non-co-directional monitoring point is located; Step S204: Use a wind speed sensor to obtain the wind direction at each environmental monitoring point respectively; for any environmental monitoring point, when the included angle between the wind direction at the environmental monitoring point and the in-field direction is less than 90°, mark the environmental monitoring point as a variable detection point; Step S205: When the included angle between the wind direction at the environmental monitoring point and the in-field direction is equal to 90°, mark the environmental monitoring point as a permanent detection point.

[0024] Step S3: Import the real-time sensing data of the wind speed sensor and the wind direction positioning method into AI, and based on AI, obtain the environmental monitoring points and wind speed monitoring points in real time, and update the in-field wind speed standard, permanent detection points, and variable detection points; manage the environment of the breeding duck farm based on the latest permanent detection points and variable detection points; Step S3 includes: Step S301: Import the real-time sensing data of the off-site sensor and the wind direction positioning method into AI; based on AI data processing, update the environmental monitoring points and wind speed monitoring points in the duck house area in real time, and update the in-field wind speed standard and variable detection points based on the latest obtained environmental monitoring points and wind speed monitoring points, where the positions of the permanent detection points remain unchanged; Step S302: Place environmental sensors at the permanent detection points and the latest variable detection points, and adjust the ventilable area of the duck house based on the sensing data of the environmental sensors until the data of all environmental sensors are standard data, where the standard data is the environmental data that allows the breeding ducks to grow normally.

[0025] Example 3, please refer to Figure 5 as shown in Figure 5 illustrates a schematic structural diagram of an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus. The memory stores computer-readable instructions, and the processor can call the instructions in the memory. When the computer-readable instructions are executed by the processor, the steps in the optimization method for managing the environment of the breeding duck farm based on AI analysis are run to achieve the following functions: First, obtain the site design drawing of the breeding duck farm and obtain the ventilable peripheral area; place wind speed sensors in the ventilable peripheral area, and use the wind direction positioning method based on the sensing data of the wind speed sensors to obtain the environmental monitoring points and wind speed monitoring points in the breeding duck farm, and also screen the wind speed monitoring points based on the wind speed sensors, and obtain the in-field wind speed standard based on the screening results; then screen the environmental monitoring points based on the in-field wind speed standard, and obtain the permanent detection points and variable detection points based on the screening results; import the real-time sensing data of the wind speed sensor and the wind direction positioning method into AI, obtain the environmental monitoring points and wind speed monitoring points in real time based on AI, and update the in-field wind speed standard, permanent detection points, and variable detection points; finally, manage the environment of the breeding duck farm based on the latest permanent detection points and variable detection points.

[0026] In addition, when the logical instructions in the above-mentioned memory are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0027] Embodiment 4, this application also provides a computer-readable storage medium. This application provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, it runs the steps in the above-mentioned method for optimizing the management of the breeding duck farm environment based on AI analysis to achieve the following functions: First, obtain the site design drawing of the breeding duck farm and obtain the ventilable peripheral area; place a wind speed sensor in the ventilable peripheral area, and use the wind direction positioning method based on the sensing data of the wind speed sensor to obtain the environmental monitoring points and wind speed monitoring points in the breeding duck farm, and also screen the wind speed monitoring points based on the wind speed sensor, and obtain the in-farm wind speed standard based on the screening results; then screen the environmental monitoring points based on the in-farm wind speed standard, and obtain the permanent detection points and variable detection points based on the screening results; import the real-time sensing data of the wind speed sensor and the wind direction positioning method into the AI, and obtain the environmental monitoring points and wind speed monitoring points in real time based on the AI, and update the in-farm wind speed standard, permanent detection points, and variable detection points; finally, manage the environment of the breeding duck farm based on the latest permanent detection points and variable detection points.

[0028] Through the description of the above embodiments, the embodiments of the present invention can be provided as a method, a system, or a computer program product. Based on this understanding, the above technical solution, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disks, optical discs, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments.

[0029] In the embodiments provided in the present application, it should be understood that the disclosed system or method can be implemented in other ways. The above-described embodiments are merely illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For another example, multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some communication interfaces. The indirect coupling or communication connection of systems, modules, and units can be in electrical, mechanical, or other forms.

[0030] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. The environmental management optimization method of the breeding duck farm based on AI analysis is characterized by: The steps include: Obtain a site design drawing of the breeding duck farm, and obtain a ventilated peripheral area of ​​the breeding duck farm based on the site design drawing; place a wind speed sensor in the ventilated peripheral area, and use a wind direction positioning method based on the sensor data of the wind speed sensor to obtain environmental monitoring points and wind speed monitoring points in the breeding duck farm; The wind speed monitoring points are screened based on the wind speed sensor, and the on-site wind speed standard is obtained based on the screening results, wherein the on-site wind speed standard includes the on-site direction and the on-site wind speed; the environmental monitoring points are screened based on the on-site wind speed standard, and the permanent detection points and the variable detection points are obtained based on the screening results; The real-time sensing data of the wind speed sensor and the wind direction positioning method are imported into AI. Based on AI, the environmental monitoring points and wind speed monitoring points are obtained in real time, and the wind speed standards, permanent detection points and variable detection points in the farm are updated. The breeding duck farm environment is managed based on the latest permanent detection points and variable detection points.

2. The method for optimizing duck farm environment management based on AI analysis according to claim 1 is characterized in that: Obtain the site design drawing of the breeder duck farm, and obtain the ventilated peripheral area of ​​the breeder duck farm based on the site design drawing, including: Obtain the site design drawing of the breeding duck farm, and record the area where the duck house is located in the site design drawing as the duck house area; record the area in the duck house area where air circulation is allowed as the ventilated area, and record the closed figure corresponding to the boundary of the duck house in the site design drawing as the duck house edge area; record the area where the ventilated area overlaps with the duck house edge area as the ventilated peripheral area; All independent areas in the ventilated peripheral area are respectively recorded as ventilated sub-areas KZ1 to ventilated sub-areas KZ v ; For any ventilated sub-area KZ b , the ventilated sub-area KZ b The points that overlap with the edge area of ​​the duck house are recorded as boundary overlap point A and boundary overlap point B, where b is a positive integer less than or equal to v and greater than or equal to 1; the distance between the boundary overlap point A and the boundary overlap point B is recorded as the sub-area length.

3. The method for optimizing duck farm environment management based on AI analysis according to claim 2 is characterized in that: Placement of wind speed sensors in ventilated peripheral areas including: When the sub-area length is greater than L, the value obtained by dividing the sub-area length by L and rounding up is recorded as j, and j points are evenly obtained in the line connecting the boundary coincidence point A and the boundary coincidence point B, and all are recorded as wind speed placement points; when the sub-area length is less than or equal to L, the midpoint of the line connecting the boundary coincidence point A and the boundary coincidence point B is recorded as the wind speed placement point, where L is the minimum installation interval of the wind speed sensor; The wind speed placement points of all ventilated sub-areas KZ are obtained, wind speed sensors are placed at the wind speed placement points, and are recorded as off-site sensors.

4. The method for optimizing duck farm environment management based on AI analysis according to claim 3 is characterized in that: Wind direction positioning methods include: The sensing data of all off-site sensors are recorded as wind speed sensing data; a plane rectangular coordinate system with the unit of the X-axis and the unit of the Y-axis both in m is established and recorded as the ventilation analysis coordinate system; the duck house area is placed in equal proportion in the ventilation analysis coordinate system and the position of the wind speed placement point is marked.

5. The method for optimizing duck farm environment management based on AI analysis according to claim 4 is characterized in that: Wind direction positioning also includes: In the ventilation analysis coordinate system: for any wind speed sensor data obtained at one time, the wind speed and wind direction are marked at the wind speed placement point based on the location of the off-site sensor. A ray is made at the wind speed placement point based on the wind direction and recorded as a ventilation ray. The direction of the ventilation ray is the direction of the wind direction. Obtain the ventilation rays corresponding to the wind speed sensor data; record the intersection of all ventilation rays in the duck house area as wind speed monitoring points, and record the number of wind speed monitoring points as k; record the independent areas divided by all ventilation rays in the duck house area as regular areas, and record the first k regular areas in all regular areas arranged from large to small as regular detection areas; obtain the center of the minimum circumscribed circle of all regular detection areas, and record it as the environmental monitoring point.

6. The method for optimizing duck farm environment management based on AI analysis according to claim 5 is characterized in that: The wind speed monitoring points are screened based on the wind speed sensor, and the wind speed standards in the field are obtained based on the screening results, including: Place wind speed sensors at all wind speed monitoring points and record them as on-site sensors; mark the wind speed and wind direction at the wind speed monitoring points based on the sensing data of the on-site sensors; for any wind speed monitoring point: when the wind direction marked at the wind speed monitoring point is the same as the direction of the ventilation ray where the wind speed monitoring point is located, the wind speed monitoring point is recorded as a same-direction monitoring point; when the wind direction marked at the wind speed monitoring point is different from the direction of the ventilation ray where the wind speed monitoring point is located, the wind speed monitoring point is recorded as a different-direction monitoring point; When the number of same-direction monitoring points is greater than that of different-direction monitoring points, the same-direction analysis algorithm is used to obtain the same-direction wind difference of each same-direction monitoring point, and the marked wind speed and wind direction of the same-direction monitoring point corresponding to the largest same-direction wind difference are recorded as the in-field wind speed and in-field wind direction, respectively. The same-direction analysis algorithm is: Z=Z0-Z1, Z is the same-direction wind difference, Z0 is the marked wind speed of the same-direction monitoring point, and Z1 is the marked wind speed of the wind speed placement point in the ventilation ray where the same-direction monitoring point is located; When the number of same-direction monitoring points is less than or equal to the number of different-direction monitoring points, the different-direction analysis algorithm is used to obtain the different-direction wind difference of each different-direction monitoring point, and the marked wind speed and wind direction of the different-direction monitoring point corresponding to the largest different-direction wind difference are recorded as the in-field wind speed and in-field wind direction, respectively. The different-direction analysis algorithm is: D=d-β, where D is the different-direction wind difference, β is the marked wind speed of the wind speed placement point in the ventilation ray where the different-direction monitoring point is located, and d is the component of the marked wind speed of the different-direction monitoring point in the direction of the ventilation ray where the different-direction monitoring point is located.

7. The method for optimizing duck farm environment management based on AI analysis according to claim 6 is characterized in that: The environmental monitoring points are screened based on the on-site wind speed standard, and the permanent detection points and variable detection points are obtained based on the screening results, including: Use wind speed sensors to obtain the wind direction of each environmental monitoring point; for any environmental monitoring point, when the angle between the wind direction of the environmental monitoring point and the direction in the field is less than 90°, the environmental monitoring point is recorded as a change detection point; When the angle between the wind direction at the environmental monitoring point and the direction within the field is equal to 90°, the environmental monitoring point is recorded as a permanent detection point.

8. The method for optimizing duck farm environment management based on AI analysis according to claim 7 is characterized in that: Management of the breeding duck farm environment based on the latest permanent detection points and variable detection points includes: The real-time sensing data and wind direction positioning method of off-site sensors are imported into AI; based on AI data processing, the environmental monitoring points and wind speed monitoring points in the duck house area are updated in real time, and the wind speed standards and change detection points in the field are updated based on the latest acquired environmental monitoring points and wind speed monitoring points, among which the position of the permanent detection point remains unchanged.

9. The method for optimizing duck farm environment management based on AI analysis according to claim 8, characterized in that: Management of the breeding duck farm environment based on the latest permanent detection points and variable detection points also includes: Environmental sensors are placed at permanent detection points and the latest change detection points, and the ventilated area of ​​the duck house is adjusted based on the sensing data of the environmental sensors until the data of all environmental sensors are standard data, wherein the standard data is environmental data that allows the normal growth of breeding ducks.

10. A duck farm environmental management optimization system based on AI analysis, used to implement the duck farm environmental management optimization method based on AI analysis according to any one of claims 1 to 9, characterized in that: Including wind speed environment detection module, environmental analysis fixed-point module and AI management optimization module; The wind speed environment detection module is used to obtain the site design drawing of the breeding duck farm, and obtain the ventilated peripheral area of ​​the breeding duck farm based on the site design drawing; place a wind speed sensor in the ventilated peripheral area, and use the wind direction positioning method based on the sensor data of the wind speed sensor to obtain the environmental monitoring points and wind speed monitoring points in the breeding duck farm; The environmental analysis fixed-point module is used to screen the wind speed monitoring points based on the wind speed sensor, and obtain the on-site wind speed standard based on the screening results, wherein the on-site wind speed standard includes the on-site direction and the on-site wind speed; screen the environmental monitoring points based on the on-site wind speed standard, and obtain the permanent detection points and the variable detection points based on the screening results; The AI ​​management optimization module is used to import the real-time sensing data of the wind speed sensor and the wind direction positioning method into AI, obtain the environmental monitoring points and wind speed monitoring points in real time based on AI, and update the wind speed standards, permanent detection points and variable detection points in the farm; manage the breeding duck farm environment based on the latest permanent detection points and variable detection points.

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