Method and system for controlling environment of henhouse

Abstract

The application provides a henhouse environment control method and system, and belongs to the technical field of intelligent control. The method comprises the following steps: matching preset environment parameter thresholds with secondary micro-partition data based on chicken growth stage data to obtain partition basic environment control data corresponding to each secondary micro-partition; correcting the partition basic environment control data based on henhouse external environment data to determine partition target environment control data corresponding to each secondary micro-partition; extracting partition environment data in the secondary micro-partition data and comparing and calculating the partition environment data with the partition target environment control data to determine partition environment deviation data of each secondary micro-partition; and determining partition regulation mode data corresponding to each secondary micro-partition based on the partition environment deviation data. The application can improve the environment control level of large-scale chicken breeding and ensure the health of chicken flocks.

Description

Technical Field

[0001] This application belongs to the field of intelligent control technology, and more specifically, relates to a method and system for controlling the environment of a chicken coop. Background Technology

[0002] Currently, most existing chicken house environmental control methods adopt a unified control model for the entire house, adjusting by preset fixed environmental parameters or simply based on single environmental data. However, this existing technology has significant drawbacks: first, fixed parameters cannot adapt to the dynamic growth needs of the flock, easily leading to stress responses and affecting production performance; second, it does not consider the impact of changes in the external environment on the internal environment control, relying solely on fixed standards, which easily causes a disconnect between the internal and external environments, resulting in low control accuracy and increased energy consumption and disease risks in the flock. Therefore, there is an urgent need for a chicken house environmental control method that can overcome the above-mentioned shortcomings of existing technologies, adapt to the growth needs of the flock, and provide precise control. Summary of the Invention

[0003] To address the aforementioned technical problems, this application provides a method and system for controlling the environment of chicken houses, thereby improving the level of environmental control in large-scale chicken farming and ensuring the health of the flock.

[0004] The embodiments of this application disclose the following technical solutions: Firstly, a method for controlling the environment of a chicken coop is provided, including: The physical spatial structure data of the chicken house is divided into regions to obtain multiple primary partition data and multiple secondary partition data; based on the flock density, each secondary partition data is further divided into micro-regions to obtain multiple secondary micro-partition data; the multiple primary partition data includes aisle area data, and the multiple secondary partition data includes breeding area data; Based on the data of the chicken flock's growth stage, preset environmental parameter thresholds are matched to the data of each secondary micro-region to obtain the basic environmental control data of each secondary micro-region. Based on the external environment data of the chicken coop, the basic environmental control data of the partition is corrected to determine the target environmental control data of each secondary micro-partition. Extract the partition environment data from each secondary micro-partition data, and compare and calculate the partition environment deviation data of each secondary micro-partition based on the partition environment data and the partition target environment control data; Based on the partition environment deviation data, the partition control mode data corresponding to each secondary micro-partition is determined.

[0005] Secondly, a chicken coop environment control system is provided, including: The region division module is used to divide the physical spatial structure data of the chicken house into regions, resulting in multiple primary-level region data and multiple secondary-level region data; based on the flock density, each secondary-level region data is further divided into micro-regions, resulting in multiple secondary-level micro-region data; the multiple primary-level region data includes aisle area data, and the multiple secondary-level region data includes breeding area data; The partition basic environment matching module is used to match preset environmental parameter thresholds to the data of each secondary micro-partition based on the data of the chicken flock growth stage, so as to obtain the partition basic environment control data corresponding to each secondary micro-partition. The partition target environment correction module is used to correct the partition basic environment control data based on the chicken house external environment data, and determine the partition target environment control data corresponding to each secondary micro-partition; The partition environment deviation calculation module is used to extract partition environment data from each secondary micro-partition data, and compare the partition environment data with the partition target environment control data to determine the partition environment deviation data of each secondary micro-partition. The partition control module is used to determine the partition control mode data corresponding to each secondary micro-partition based on the partition environment deviation data.

[0006] Thirdly, embodiments of this application also provide an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the chicken coop environment control method provided in any possible implementation of the first aspect.

[0007] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the chicken coop environment control method provided by any possible implementation of the first aspect.

[0008] The beneficial effects of the technical solution provided in this application are as follows: Compared with related technologies, the chicken house environment control method and system provided in this application adopt a spatial division method combining primary zoning and secondary micro-zoning. Independent breeding units are set up according to the chicken density, ensuring that the environmental control within the house matches the actual breeding distribution. This avoids local environmental anomalies caused by spatial differences and structurally improves the defect of poor environmental uniformity within the chicken house. By matching preset environmental parameters according to the chicken's growth stage, this application can accurately adapt to the physiological needs of different growth cycles, overcoming the shortcomings of traditional fixed parameter control that cannot meet the needs of staged breeding, and significantly reducing the probability of stress in the chicken flock.

[0009] Meanwhile, this application dynamically corrects basic environmental parameters using external environmental data, making the target environmental control data more closely match actual working conditions and improving the rationality and accuracy of environmental regulation. By comparing zoned environmental data with zoned target environmental control data in real time, environmental deviations are quickly generated and control modes are determined, enabling rapid response and precise adjustment of environmental parameters, ensuring that the environment inside the chicken house is always maintained within a suitable range. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 A schematic diagram of a chicken coop provided in an embodiment of this application; Figure 2 A schematic flowchart of the chicken coop environment control method provided in the embodiments of this application; Figure 3 A structural block diagram of the chicken coop environmental control system provided in the embodiments of this application; Figure 4 A schematic block diagram of a computer device provided in an embodiment of this application; Figure 5 Another schematic block diagram of the computer device provided in the embodiments of this application. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0013] It should be noted that the terms "first," "second," and similar terms used in this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Unless the context clearly indicates otherwise, the singular forms "a," "one," or "the," etc., do not indicate a quantity limitation, but rather indicate the presence of at least one. The quantities of "multiple" or "multiple copies" mentioned in the embodiments of this application all refer to a quantity of "at least two," for example, "multiple" means "at least two," and "multiple copies" means "at least two copies." The terms "comprising" and "having," and any variations thereof, as used in this application, are intended to cover non-exclusive inclusion. The term "and / or" as used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0014] like Figure 2 As shown in the embodiments of this application, the chicken coop environment control method can be executed by computer equipment in each step. Computer equipment refers to electronic equipment with data computing, processing, and storage capabilities. The method may include: S101: Divide the physical spatial structure data of the chicken house into regions to obtain multiple primary partition data and multiple secondary partition data; divide each secondary partition data into micro-regions based on the flock density to obtain multiple secondary micro-partition data; the multiple primary partition data include aisle area data, and the multiple secondary partition data include breeding area data.

[0015] In this embodiment, the physical spatial structure data of the chicken house refers to a set of parameters that characterize the actual physical dimensions, spatial layout, wall positions, ventilation distribution, and other spatial features of the chicken house. These parameters are obtained by digital acquisition using a laser rangefinder or architectural drawings, with an acquisition accuracy of millimeters, ensuring the accuracy of area division.

[0016] This embodiment uses a spatial grid partitioning method to process the physical spatial structure data of the chicken house. First, it completes the first-level partitioning according to functional attributes, dividing the chicken house into a passageway area and a breeding area, such as... Figure 1 As shown, the passageway area is the passageway for chicken feeding operations, and the breeding area is the core area for chicken breeding. The breeding area is further divided into secondary micro-regions according to the chicken density, which is the number of chickens per unit area. Based on a breeding density standard of 5-15 chickens per square meter, the breeding area is divided into several independent secondary micro-regions. Each secondary micro-region is an independent breeding unit that is closed or semi-closed, with an area of ​​10-20 square meters. Each secondary micro-region is equipped with independent environmental monitoring and control equipment.

[0017] Specifically, the process begins by collecting physical spatial structure data of the chicken house. This is achieved through digitization of architectural drawings combined with on-site data collection using a laser rangefinder, obtaining complete spatial parameters such as the size, layout, and wall distribution of the chicken house. Next, a zone division operation is performed. The collected spatial structure data is processed using a spatial grid division method, dividing the chicken house space into passageway areas and breeding areas according to functional attributes, simultaneously generating corresponding primary and secondary zone data. Then, chicken density data is acquired. Based on breeding planning standards and actual breeding needs, the chicken density of the breeding area is determined, and the number of chickens per unit area is calculated by the breeding area and the planned number of chickens. Finally, a micro-region division operation is performed. Based on the determined chicken density, a division threshold is set, and the secondary zone data corresponding to the breeding area is spatially segmented, dividing the breeding area into several independent small areas that meet the density requirements. Simultaneously, secondary micro-zone data corresponding to each independent small area is generated, completing the multi-level division of the entire chicken house space.

[0018] In this embodiment, by dividing the chicken house into primary and secondary zones according to function, the core breeding area and auxiliary functional areas are clearly defined, avoiding interference from passageways with the environmental control of the breeding area and ensuring the targeted nature of environmental control. The breeding area is further subdivided into micro-regions based on flock density, ensuring that the resulting secondary micro-zones match the actual density distribution characteristics of the breeding. This provides accurate spatial data support for subsequent precise zoning control of the chicken house environment, effectively avoiding the problem of poor environmental adaptability caused by uniform control of the entire house, and improving the precision of chicken house environmental control.

[0019] S102: Based on the data of the chicken flock's growth stage, match the preset environmental parameter thresholds to the data of each secondary micro-partition to obtain the basic environmental control data of each secondary micro-partition.

[0020] In this embodiment, the data on the growth stages of the chicken flock are parameters based on the age of the flock, including the brooding period (1-21 days old), the rearing period (22-140 days old), and the laying period (141 days old and above). These parameters are entered by the farmers or automatically generated by the chicken flock management system. The preset environmental parameter thresholds are temperature and humidity ranges pre-set according to the physiological needs of different chicken flock growth stages. The temperature threshold for the brooding period is 32-36℃, and the humidity threshold is 55-75%; the temperature threshold for the rearing period is 18-24℃, and the humidity threshold is 50-60%; and the temperature threshold for the laying period is 20-25℃, and the humidity threshold is 45-55%. These thresholds are stored in the chicken house environmental control database. The basic environmental control data for each zone is generated by matching each secondary micro-zone with the preset environmental parameter thresholds corresponding to the chicken flock growth stage. The matched preset environmental parameter thresholds are directly used as the data for the corresponding secondary micro-zone, and the data format is specific temperature and humidity values ​​or ranges.

[0021] In this embodiment, the correspondence between chicken flock growth stage data and preset environmental parameter thresholds is first sorted and stored. These preset environmental parameter thresholds are formulated based on industry standards for large-scale chicken farming and research findings on chicken flock physiology, and are categorized by brooding period, rearing period, and laying period. Next, all secondary micro-zone data generated after the chicken house space division is retrieved, and a unique spatial identifier for each secondary micro-zone is identified. Then, according to the actual breeding plan, corresponding chicken flock growth stage data is assigned to each secondary micro-zone, achieving a correspondence between breeding stages and breeding units. Afterwards, a matching operation is performed, using data association to map each secondary micro-zone data to the preset environmental parameter thresholds corresponding to the assigned growth stage. Finally, the matched preset environmental parameter thresholds are extracted and used as the basic environmental control data for each secondary micro-zone. All data is then organized and stored uniformly, providing data support for subsequent correction processing.

[0022] This embodiment uses two-level micro-zones as units, combining data from the chicken flock's growth stages with preset environmental parameter thresholds. This ensures that the basic environmental control data for each micro-zone accurately matches the chicken flock's growth and physiological needs, solving the problem that traditional uniform environmental parameters cannot meet the needs of chicken flocks at different growth stages. Simultaneously, it applies basic environmental control standards to specific breeding units, laying a precise and realistic foundation of data for subsequent differentiated environmental adjustments. This enhances the targeted nature of chicken house environmental control, provides a guarantee for refined environmental regulation, and reduces the probability of stress responses in chicken flocks due to environmental discomfort.

[0023] In this embodiment, based on the chicken flock growth stage data, preset environmental parameter thresholds are matched to the data of each secondary micro-region to obtain the basic environmental control data of each secondary micro-region, including: The correlation between chicken flock growth stage data and preset environmental parameter thresholds is processed to obtain stage-threshold correspondence data; a stage-threshold mapping library is determined based on the stage-threshold correspondence data. Each secondary micro-partition data is assigned a unique spatial identifier to obtain each identifiable secondary micro-partition data; each identifiable secondary micro-partition data is then standardized to obtain each standardized secondary micro-partition data. Based on the standardized secondary micro-partition data, the appropriate chicken flock growth stage data is determined; the standardized secondary micro-partition data and the appropriate chicken flock growth stage data are bound together to obtain stage-partition bound data. Based on the stage-partition binding data retrieval stage-threshold mapping library, the corresponding preset environment parameter threshold is determined; the stage-partition binding data and the corresponding preset environment parameter threshold are associated to obtain stage-partition-threshold associated data. Based on the stage-partition-threshold correlation data, the preset environmental parameter thresholds are extracted to determine the basic environmental control data of each secondary micro-partition.

[0024] In this embodiment, based on industry standards for large-scale chicken farming and the physiological tolerance characteristics of chickens at different growth stages, corresponding preset environmental parameter thresholds are set according to the chicken growth stage data, such as the brooding period, growing period, and laying period. These thresholds include suitable ranges for core environmental indicators such as temperature and humidity. A structured data storage method is adopted, using data from each growth stage as index keys and the corresponding preset environmental parameter thresholds as index values ​​to establish a one-to-one stage-threshold mapping library. This mapping library supports threshold updates based on the breed and region of the chicken house. All secondary micro-zone data generated after the chicken house space is divided are retrieved. Based on the coordinate system of the chicken house's physical spatial structure data, a unique spatial identifier is assigned to each secondary micro-zone, containing features such as the micro-zone's spatial location and region number. The secondary micro-zone data is standardized, unifying data format, spatial dimensions, and other parameters to ensure that each micro-zone has identifiable and associative uniqueness. Based on the actual breeding plan and the flock grouping scheme, corresponding flock growth stage data is assigned to each secondary micro-zone with a unique spatial identifier. The binding process adopts a one-to-one directional matching method of "spatial unit - breeding stage," which can bind different secondary micro-zone data with different flock growth stage data according to actual breeding needs, supporting the zoned breeding of multi-stage flocks in the same shed. Based on the secondary micro-zone data with completed growth stage binding, the flock growth stage data bound to each micro-zone is used as the search condition to accurately search in the established stage-threshold mapping library and extract the preset environmental parameter threshold corresponding to the growth stage. The association process uses the secondary micro-zone as the smallest execution unit, and each micro-zone independently completes the search and association, ensuring that the association results accurately match the breeding stage of the micro-zone. The preset environmental parameter thresholds after the data of each secondary micro-partition are extracted are used as the basic environmental control data of the corresponding secondary micro-partition. The generated basic environmental control data of the partition is permanently bound to the unique spatial identifier of the corresponding secondary micro-partition and stored in a structured database. The basic environmental control data of each secondary micro-partition can be quickly retrieved in the database through the unique spatial identifier, providing accurate basic data support for subsequent environmental data correction and deviation calculation.

[0025] S103: Based on the external environment data of the chicken house, the basic environmental control data of the partition is corrected and processed to determine the target environmental control data of each secondary micro-partition.

[0026] In this embodiment, the external environmental data of the chicken house refers to the real-time temperature and humidity data outside the chicken house, collected by temperature and humidity sensors installed in an unobstructed location outside the chicken house, with a collection frequency of once per minute. The correction process uses numerical calculations to adjust the basic environmental control data of each zone based on changes in the external environmental data, making the adjusted environmental data more closely match the actual breeding environment of the chicken house. The target environmental control data for each zone is the final temperature and humidity control data that each secondary micro-zone needs to achieve after correction based on the external environmental data; these are specific temperature and humidity values.

[0027] In this embodiment, the basic environmental control data for each zone is corrected based on the external environmental data of the chicken coop, and the target environmental control data for each secondary micro-zone is determined, including: The raw signals collected by the outdoor temperature and humidity sensor of the chicken house are acquired, and the raw signals are subjected to analog-to-digital conversion and filtering to obtain standardized external environmental data. Environmental correction coefficients are determined based on standardized external environmental data. The correction coefficients are then calculated with the basic environmental control data of the zoning area to obtain the correction benchmark value. Different position correction weights are assigned based on the position differences of each secondary micro-partition. The position correction weights are then weighted and calculated with the correction benchmark value to obtain the target correction value. The partition basic environmental control data and the target correction value are superimposed to obtain the partition target environmental control data corresponding to each secondary micro-partition.

[0028] In this embodiment, the environmental correction coefficient is a proportional coefficient calculated based on standardized external environmental data and used to adjust the basic environmental control data of the zoning area. The coefficient value is between 0.8 and 1.2, determined by comparing the standardized external environmental data with the environmental tolerance threshold of the chicken flock at its growth stage. Location difference refers to the different spatial positions of each secondary micro-zone within the chicken house's rearing area, mainly divided into air inlet, middle, and outlet. The air inlet is the area close to the chicken house's ventilation openings, the middle is the central area of ​​the rearing area, and the outlet is the area far from the chicken house's ventilation openings. The location correction weight is a numerical weight assigned based on the location differences of the secondary micro-zones: 1.1 for the air inlet, 1.0 for the middle, and 0.9 for the outlet. This weight is set according to the airflow distribution pattern of the chicken house's ventilation system to adapt to the environmental change characteristics of different locations.

[0029] For example, this embodiment first collects raw environmental signals using an outdoor temperature and humidity sensor, converts the analog signals into processable digital signals through analog-to-digital conversion, and then filters out abnormal data to obtain standardized external environmental data, providing clean and accurate basic data for determining subsequent correction coefficients. Environmental correction coefficients are calculated based on the standardized external environmental data, and these coefficients are multiplied by the basic environmental control data for each zone to obtain a correction benchmark value, achieving initial unified correction of the basic data. Next, corresponding location correction weights are assigned according to the location differences of each secondary micro-zone, and weighted calculations are used to achieve differentiated adjustments to the correction benchmark value, adapting to the environmental requirements of different location micro-zones. Finally, the basic environmental control data is superimposed with the target correction value to obtain the specific target environmental control data for each secondary micro-zone.

[0030] In this embodiment, determining the environmental correction coefficient based on standardized external environmental data includes: The standardized external environment data is smoothed over time to obtain the average outdoor environment data. The difference between the average outdoor environmental data and the environmental tolerance threshold corresponding to the growth stage of the chicken flock is calculated to obtain the environmental deviation benchmark value. Based on the ventilation status of each secondary micro-zone, the ventilation adjustment coefficient corresponding to each secondary micro-zone is assigned. The environmental deviation benchmark value is weighted and calculated with the ventilation adjustment coefficient. The environmental correction coefficients corresponding to each secondary micro-partition are obtained.

[0031] In this embodiment, time-dimensional smoothing is a continuous processing of standardized external environmental data over time to eliminate short-term fluctuations in environmental data, making the data more reflective of the true changing trends of the outdoor environment. The average outdoor environmental data refers to the average values ​​of temperature and humidity outside the chicken house over a certain period, obtained after time-dimensional smoothing. The data units are ℃ (temperature) and % (humidity). Ventilation status refers to the airflow within each secondary micro-zone. Based on the number of vents, fan power, and air velocity, it is divided into three levels: good ventilation, moderate ventilation, and poor ventilation. An air velocity ≥0.5 m / s is considered good ventilation, 0.3-0.5 m / s is moderate ventilation, and <0.3 m / s is poor ventilation. This is determined by collecting air velocity data from each secondary micro-zone using a wind speed sensor. The ventilation adjustment coefficient is a numerical coefficient assigned based on the ventilation status of each secondary micro-zone: 0.9 for good ventilation, 1.0 for moderate ventilation, and 1.1 for poor ventilation. This coefficient is used to adapt to the environmental correction needs under different ventilation conditions.

[0032] Exemplarily, in this embodiment, the standardized external environmental data is first smoothed in the time dimension to eliminate the data error caused by instantaneous environmental fluctuations, and the outdoor environmental mean data reflecting the true outdoor environmental state is obtained, providing stable basic data for the calculation of the correction coefficient; the difference operation is performed between the outdoor environmental mean data and the environmental tolerance threshold of the chicken growth stage to obtain an environmental deviation reference value reflecting the difference between the external environment and the chicken tolerance environment, and this value is the core calculation basis for the correction coefficient; then, according to the actual ventilation status of each secondary microzone, a corresponding ventilation adjustment coefficient is assigned to each microzone to adapt to the ventilation environmental differences in each area; finally, the environmental deviation reference value and the ventilation adjustment coefficient are weighted and normalized to obtain the environmental correction coefficient exclusive to each secondary microzone.

[0033] In this embodiment, performing the time - dimension smoothing process on the standardized external environmental data to obtain the outdoor environmental mean data includes: Constructing a sliding time window; Calculating the mean value of the standardized external environmental data within the sliding time window to obtain the outdoor environmental mean data.

[0034] In this embodiment, the process of constructing the sliding time window is as follows: The standardized external environmental data includes temperature parameters and humidity parameters, and the data acquisition frequency is F (unit: times / second); the basic duration of the sliding time window is T0 (unit: second); the sliding step is ΔT (unit: second, ΔT < T0); the time decay factor is α (value range 0 < α ≤ 1), and the closer to the current acquisition time, the smaller the time decay factor; let the starting acquisition time of the m - th sliding time window (m is a positive integer, m = 1, 2, 3...) be t m =(m - 1)×ΔT, and the ending acquisition time is t m ′=t m +T0, forming the window time interval [t m ,t m ′].

[0035] Within the window time interval, all the standardized external environmental data whose acquisition times fall within it are screened out. Denote the acquisition time of a single piece of data as t i , then the time decay weight of this piece of data is ω i =α(t m ′ - t i ); at the same time, the abnormal data whose values exceed the reasonable range of the outdoor temperature and humidity in the chicken house are excluded to obtain the effective data sample set D m , denote the amount of effective data in the sample set as n(D m ), set the minimum effective sample number N min =F×T0×0.75, and the shortest length of the continuous effective data segment needs to satisfy L≥F×T0×0.5.

[0036] If n(D) m )≥N min If the requirement for continuous valid data segment length is met, then the m-th sliding time window is considered complete; otherwise, the base duration T0 is iteratively expanded by a factor of 1.2, and the termination acquisition time t is recalculated. m And filter the valid data sample set D m The sliding time window is constructed until the dual judgment conditions are met.

[0037] This embodiment first constructs a sliding time window, such as 1 hour, based on the collection frequency of standardized external environmental data, to determine the time range and sample size for data processing, thus giving the data processing a standardized time boundary. As outdoor temperature and humidity data are continuously collected, the sliding time window slides backward, always processing the latest 1-hour standardized external environmental data. The arithmetic mean of all data samples within the sliding time window is calculated to obtain the average values ​​of temperature and humidity, which are the average outdoor environmental data.

[0038] The external environment directly impacts the environment inside the chicken house. Basic control data alone cannot adapt to changes in external climate; therefore, adjustments must be made in conjunction with external environmental data to ensure the target data better reflects actual operating conditions. Standardizing the raw signals ensures the accuracy of the external environmental data and prevents interference from affecting the correction effect. Assigning differentiation coefficients and weights based on location and ventilation status takes into account the varying degrees of external influence on different micro-zones within the chicken house, as uniform correction cannot accommodate regional differences. Time-dimension smoothing eliminates instantaneous fluctuations in the external environment, allowing the correction to better align with real-world environmental trends, ultimately achieving precise and differentiated correction for each micro-zone.

[0039] For example, firstly, raw environmental signals are continuously collected using outdoor temperature and humidity sensors at a frequency of once per minute. The raw signals undergo analog-to-digital conversion and filtering to convert analog electrical signals into digital signals. Abnormal data is then eliminated by averaging multiple consecutive data acquisitions to obtain standardized external environmental data. Next, a fixed-duration sliding time window is constructed, and the average of the standardized external environmental data within the window is calculated to obtain the average outdoor environmental data. This data is then compared with the environmental tolerance threshold corresponding to the chickens' growth stage to obtain the environmental deviation baseline value. Next, ventilation adjustment coefficients are assigned based on the ventilation status of each secondary micro-zone, and the two are weighted to obtain the environmental correction coefficient. The environmental correction coefficient is then calculated with the basic environmental control data for each zone to obtain the correction baseline value. Based on the location differences of each secondary micro-zone, location correction weights are assigned, and these are weighted with the correction baseline value to obtain the target correction value. Finally, the basic environmental control data for each zone and the target correction value are superimposed to obtain the target environmental control data for each secondary micro-zone.

[0040] This embodiment effectively eliminates interference and anomalies in environmental data through standardized processing of raw outdoor signals, ensuring the accuracy of external environmental data and providing a reliable basis for correction processing. Combined with smoothing processing using a sliding time window, the impact of instantaneous fluctuations in the external environment is eliminated, making the correction basis more closely aligned with real environmental trends. Differential correction is achieved through location correction weights and ventilation adjustment coefficients, solving the problem that uniform correction cannot adapt to the differences in micro-zone areas. This allows the corrected zone target environmental control data to accurately match the actual environmental needs of each micro-zone, improving the accuracy and rationality of chicken house environmental control.

[0041] S104: Extract the partition environment data from each secondary micro-partition data, and calculate the partition environment deviation data of each secondary micro-partition by comparing the partition environment data with the partition target environment control data.

[0042] In this embodiment, the zoned environmental data refers to the real-time temperature and humidity environmental data within each secondary micro-zone, collected by temperature and humidity sensors located at the center of each secondary micro-zone. The collection frequency can be once per minute, and this data represents the actual environmental state within the chicken house. The zoned environmental deviation data is a set of temperature and humidity deviation values ​​obtained through comparative calculation. Positive numbers indicate that the actual environmental parameters are higher than the target values, negative numbers indicate that the actual environmental parameters are lower than the target values, and zero indicates that the actual environmental parameters are consistent with the target values.

[0043] In this embodiment, environmental monitoring sensors are first deployed at the core location of each secondary micro-zone to continuously collect core environmental parameters such as temperature and humidity once per minute. The measured data from the sensors constitutes the environmental data for each secondary micro-zone. This measured environmental data is then extracted from the secondary micro-zone data and categorized according to the unique spatial identifier of each secondary micro-zone to ensure accurate association between the data and the corresponding micro-zone. Next, the identified target environmental control data for each secondary micro-zone is retrieved from the database and matched one by one with the corresponding secondary micro-zone environmental data based on the unique spatial identifier. Then, parameter-by-parameter comparison calculations are performed on the two sets of matched data, calculating the difference between the actual and target values ​​for environmental indicators such as temperature and humidity. Finally, the calculated difference values ​​are determined as the environmental deviation data for the corresponding secondary micro-zone, bound to the unique spatial identifier of the micro-zone, and stored uniformly in the database to form a complete deviation data ledger.

[0044] S105: Determine the partition control mode data corresponding to each secondary micro-partition based on the partition environment deviation data.

[0045] In this embodiment, the partition control mode data corresponding to each secondary micro-partition is determined based on the partition environment deviation data, including: The partitioned environmental deviation data is graded to obtain partitioned environmental deviation graded data. Based on the zoning environmental deviation grading data and the real-time activity status data of chicken flocks in each secondary micro-zone, the zoning control mode data corresponding to each secondary micro-zone is determined. In this embodiment, In this embodiment, based on the zoning environmental deviation grading data and the real-time activity status data of the chicken flock in each secondary micro-zone, the zoning control mode data corresponding to each secondary micro-zone is determined, including: The real-time activity status data of the chicken flock is validated to obtain valid chicken flock status data. Based on the zoning environmental deviation classification data, effective flock status data, and flock density differences in each secondary micro-zone, the corresponding zoning control mode data for each secondary micro-zone are determined.

[0046] In this embodiment, the zone control mode data refers to the environmental control parameters for each secondary micro-zone, matched based on the zone environmental deviation data. These parameters include heating mode, cooling mode, humidification mode, dehumidification mode, and steady-state mode. Different deviation data correspond to different control modes, and this correspondence is pre-stored in the control logic. The grading process divides the zone environmental deviation data into different levels based on the absolute value of the deviation. Temperature deviation data is divided into three levels based on absolute value: no deviation (absolute value ≤ 0.5℃), slight deviation (0.5℃ < absolute value ≤ 1.5℃), and severe deviation (absolute value > 1.5℃). Humidity deviation data is also divided into three levels based on absolute value: no deviation (absolute value ≤ 5%), slight deviation (5% < absolute value ≤ 10%), and severe deviation (absolute value > 10%). The zone environmental deviation grading data refers to the graded data obtained after grading, characterizing the degree of temperature and humidity deviation in each secondary micro-zone. It is one of no deviation, slight deviation, or severe deviation, directly reflecting the degree of difference between the actual environment and the target environment. The real-time activity status data of the chicken flock represents the parameter data of the real-time behavior status of the chicken flock in each secondary micro-zone, including three states: normal activity, huddling together, and open-mouth breathing. The data is obtained by collecting images of the chicken flock activity by high-definition cameras set up in each secondary micro-zone, and then processing the images through image recognition algorithms.

[0047] For example, this embodiment first classifies the environmental deviation data of each secondary micro-zone according to a preset deviation level standard, dividing it into different levels based on the absolute value of the deviation to obtain the partitioned environmental deviation classification data. Then, it collects real-time activity status data of the chicken flock in each secondary micro-zone, performs time continuity verification on this data, and removes abnormal data with frequent jumps within a short period to obtain effective chicken flock status data. Next, it retrieves the chicken flock density difference data of each secondary micro-zone to clarify the stocking density level of each area. Finally, using the partitioned environmental deviation classification data as the core basis, combined with the effective chicken flock status data, it judges the actual response of the chicken flock to the environment, and adjusts the control priority and intensity with reference to the chicken flock density difference. According to a preset multi-data matching rule, it determines the corresponding partitioned control mode data for each secondary micro-zone, binds it with the micro-zone's unique identifier, and stores it.

[0048] As can be seen from the above, this application adopts a spatial division method combining primary zoning and secondary micro-zoning, setting up independent breeding units according to the flock density. This ensures that the environmental control within the chicken house matches the actual breeding distribution, avoiding local environmental anomalies caused by spatial differences and structurally improving the defect of poor environmental uniformity within the chicken house. By matching preset environmental parameters according to the growth stage of the flock, this application can accurately adapt to the physiological needs of different growth cycles, overcoming the shortcomings of traditional fixed parameter control that cannot meet the needs of staged breeding, and significantly reducing the probability of stress in the flock.

[0049] Meanwhile, this application dynamically corrects basic environmental parameters using external environmental data, making the target environmental control data more closely match actual working conditions and improving the rationality and accuracy of environmental regulation. By comparing zoned environmental data with zoned target environmental control data in real time, environmental deviations are quickly generated and control modes are determined, enabling rapid response and precise adjustment of environmental parameters, ensuring that the environment inside the chicken house is always maintained within a suitable range.

[0050] In one embodiment of this application, when performing environmental actions based on the partition control mode data, the negative pressure of each secondary micro-partition is monitored and controlled; The negative pressure of each secondary micro-zone is monitored and adjusted, including: Real-time negative pressure data of each secondary micro-zone is obtained. Based on the negative pressure threshold corresponding to the chicken flock growth stage, the ventilation status of the secondary micro-zone, and the chicken flock density, the target negative pressure data corresponding to each secondary micro-zone is determined. The real-time negative pressure data is compared with the target negative pressure data to obtain the negative pressure deviation data; Based on the negative pressure deviation data, adjust the operating parameters of the ventilation actuators in the corresponding secondary micro-zones.

[0051] In this embodiment, real-time negative pressure data refers to the difference between the real-time air pressure in each secondary micro-zone and the external atmospheric pressure, which is collected by negative pressure sensors installed in each secondary micro-zone, with a collection frequency of once per minute. The negative pressure threshold corresponding to the chicken flock's growth stage refers to a negative pressure range preset according to the physiological needs of different growth stages. The negative pressure threshold for the brooding period is 5-8 Pa, for the growing period it is 3-5 Pa, and for the laying period it is 4-6 Pa. This threshold represents the optimal negative pressure range for chicken house ventilation, ensuring air circulation within the house while preventing the chickens from being directly exposed to airflow. Target negative pressure data refers to the negative pressure control target value for each secondary micro-zone obtained after numerical adjustment, combining the negative pressure threshold corresponding to the chicken flock's growth stage, the ventilation status of the secondary micro-zone, and the flock density. Micro-zones with poor ventilation and high density use the upper limit of the threshold range, micro-zones with good ventilation and low density use the lower limit, and micro-zones with moderate ventilation and medium density use the middle value of the threshold range. Negative pressure deviation data refers to the numerical value calculated by subtracting the real-time negative pressure data of each secondary micro-zone from the corresponding target negative pressure data. A positive number indicates that the actual negative pressure is higher than the target value, a negative number indicates that the actual negative pressure is lower than the target value, and zero indicates that the actual negative pressure is the same as the target value. Ventilation actuators refer to the equipment used to regulate the negative pressure in the chicken house, including axial flow fans and ventilation outlet regulating valves. Operating parameters refer to the working parameters of the ventilation actuators, including the operating frequency of the axial flow fan and the opening degree of the ventilation outlet regulating valves. The fan operating frequency range is 0-50Hz, and the outlet opening degree range is 0-90°.

[0052] For example, while executing environmental control actions based on the zoning control mode data, negative pressure data of each secondary micro-zone is collected in real time through negative pressure sensors to achieve real-time monitoring of negative pressure in each area; combined with the negative pressure threshold of the chicken flock's growth stage, the ventilation status of each micro-zone, and the chicken density, suitable target negative pressure data is determined for each micro-zone, so that the target negative pressure matches the actual breeding needs of each area; the difference between the real-time negative pressure data and the target negative pressure data is calculated to obtain negative pressure deviation data that reflects the difference between the actual negative pressure and the target negative pressure; based on the sign and magnitude of the negative pressure deviation data, the operating parameters of the ventilation equipment in the corresponding micro-zone are adjusted. When the actual negative pressure is higher than the target value, the fan operating frequency is reduced or the air outlet opening is decreased; when the actual negative pressure is lower than the target value, the fan operating frequency is increased or the air outlet opening is increased, thereby achieving differentiated and precise control of negative pressure in each secondary micro-zone.

[0053] In this embodiment, based on the negative pressure threshold corresponding to the chicken flock's growth stage, the ventilation status of the secondary micro-zones, and the chicken flock density, the target negative pressure data corresponding to each secondary micro-zone is determined, including: Determine the basic negative pressure threshold data based on the negative pressure threshold corresponding to the growth stage of the chicken flock; The negative pressure correction coefficient data for ventilation status is determined based on the ventilation status of the secondary micro-zones; The first correction process is performed based on the negative pressure baseline threshold data and the negative pressure correction coefficient data under ventilation status to obtain the negative pressure data after ventilation correction. Data on negative pressure correction coefficients for flock density were determined based on flock density in secondary micro-regions. A second correction process was performed based on the negative pressure data after ventilation correction and the negative pressure correction coefficient data of flock density to obtain the negative pressure data after density correction. Determine the reasonable range of negative pressure values ​​based on data from the chicken coop negative pressure control standards. The negative pressure data after density correction is subjected to value range constraint processing to obtain negative pressure data with value range constraint. After constraining the value range, the negative pressure data is standardized and calibrated to obtain the target negative pressure data corresponding to each secondary micro-partition.

[0054] In this embodiment, the negative pressure baseline threshold data is the basic control value for the negative pressure threshold conversion corresponding to the chicken flock growth stage, for example, the 8Pa negative pressure baseline threshold corresponding to the brooding period; the ventilation status negative pressure correction coefficient data is a numerical coefficient adapted to the micro-zone ventilation status, for example, a correction coefficient of 1.1 for poorly ventilated areas; the ventilation-corrected negative pressure data is the value of the baseline threshold after correction by the ventilation coefficient, for example, 8.8Pa ventilation-corrected negative pressure data. The chicken flock density negative pressure correction coefficient data is a numerical coefficient adapted to the chicken flock density of the micro-zone, for example, a correction coefficient of 1.05 for high-density areas; the negative pressure reasonable value range data is the safe control range of negative pressure in the chicken house, for example, a negative pressure reasonable value range of 3-10Pa; the value range constrained negative pressure data is the negative pressure value after verification of the safe range, for example, a value range constrained by 10Pa.

[0055] For example, firstly, based on the negative pressure threshold corresponding to the chicken flock's growth stage, numerical values ​​are directly extracted as the basic negative pressure threshold data, and categorized and organized according to the brooding period, growing period, and laying period. Next, the ventilation status of each secondary micro-zone is collected, and differential coefficients are assigned according to good, average, and poor ventilation to obtain ventilation status negative pressure correction coefficient data. This data is then calculated with the basic negative pressure threshold data to complete the first correction, resulting in ventilation-corrected negative pressure data. Next, the chicken flock density in each secondary micro-zone is statistically analyzed, and corresponding coefficients are assigned according to high, medium, and low density to obtain flock density negative pressure correction coefficient data. This data is then calculated with the ventilation-corrected negative pressure data to complete the second correction, resulting in density-corrected negative pressure data. Then, according to the chicken house negative pressure control specifications, a reasonable negative pressure value range including upper and lower limits is established. The density-corrected negative pressure data is compared with the value range; if it exceeds the range, it is adjusted to the boundary value to obtain value range-constrained negative pressure data. Finally, the data is standardized in format and unit, bound to a unique spatial identifier of the secondary micro-zone, and standardized calibration is completed to obtain the target negative pressure data corresponding to each secondary micro-zone.

[0056] As can be seen from the above, this embodiment achieves differentiated monitoring and control of negative pressure in the secondary micro-zones of the chicken house, solving the problem of uneven regional negative pressure caused by traditional uniform negative pressure control of the whole house, and ensuring that the negative pressure in each breeding area of ​​the chicken house is within a suitable range. The target negative pressure data is determined by combining the growth stage of the chicken flock, ventilation status, and flock density, so that the target negative pressure can fully meet the actual breeding needs of each micro-zone, improving the rationality and adaptability of negative pressure control. Real-time monitoring of the negative pressure in each micro-zone is achieved through negative pressure sensors, enabling timely detection of abnormal negative pressure conditions and providing timely and accurate basis for negative pressure control. The operating parameters of the ventilation equipment are precisely adjusted based on the negative pressure deviation data, realizing closed-loop control of negative pressure, ensuring the stability of the negative pressure in each micro-zone, and improving the ventilation effect of the chicken house.

[0057] Based on the same principle as the chicken coop environment control method provided in the embodiments of this application, the embodiments of this application also provide a chicken coop environment control system, such as... Figure 3 As shown, the chicken house environmental control system 20 may specifically include: a zone division module 21, a zone basic environment matching module 22, a zone target environment correction module 23, a zone environmental deviation calculation module 24, and a zone control module 25. The zone division module 21 is used to divide the physical spatial structure data of the chicken house into zones, obtaining multiple primary zone data and multiple secondary zone data; based on the flock density, each secondary zone data is further divided into micro-regions, obtaining multiple secondary micro-zone data; the multiple primary zone data includes aisle area data, and the multiple secondary zone data includes breeding area data. The partition basic environment matching module 22 is used to match preset environmental parameter thresholds to the data of each secondary micro-partition based on the data of the chicken flock growth stage, so as to obtain the partition basic environment control data corresponding to each secondary micro-partition. The partition target environment correction module 23 is used to correct the partition basic environment control data based on the chicken house external environment data, and determine the partition target environment control data corresponding to each secondary micro-partition; The partition environment deviation calculation module 24 is used to extract the partition environment data from each secondary micro-partition data, and to calculate the partition environment deviation data of each secondary micro-partition by comparing the partition environment data with the partition target environment control data. The partition control module 25 is used to determine the partition control mode data corresponding to each secondary micro-partition based on the partition environment deviation data.

[0058] In one embodiment of this application, the partition target environment correction module 23 is specifically used to acquire the raw signal collected by the outdoor temperature and humidity sensor of the chicken house, perform analog-to-digital conversion and filtering on the raw signal, and obtain standardized external environment data. Environmental correction coefficients are determined based on standardized external environmental data. The correction coefficients are then calculated with the basic environmental control data of the zoning area to obtain the correction benchmark value. Different position correction weights are assigned based on the position differences of each secondary micro-partition. The position correction weights are then weighted and calculated with the correction benchmark value to obtain the target correction value. The partition basic environmental control data and the target correction value are superimposed to obtain the partition target environmental control data corresponding to each secondary micro-partition.

[0059] In one embodiment of this application, the partition target environment correction module 23 is specifically used to perform time-dimensional smoothing processing on standardized external environment data to obtain outdoor environment mean data; The difference between the average outdoor environmental data and the environmental tolerance threshold corresponding to the growth stage of the chicken flock is calculated to obtain the environmental deviation benchmark value. Based on the ventilation status of each secondary micro-zone, the ventilation adjustment coefficient corresponding to each secondary micro-zone is assigned. The environmental deviation benchmark value is weighted and calculated with the ventilation adjustment coefficient. The environmental correction coefficients corresponding to each secondary micro-partition are obtained.

[0060] In one embodiment of this application, the partition target environment correction module 23 is specifically used to construct a sliding time window; The average value of the standardized external environment data within the sliding time window is calculated to obtain the average outdoor environment data.

[0061] In one embodiment of this application, the partition control module 25 is specifically used to perform hierarchical processing on the partition environmental deviation data to obtain partition environmental deviation hierarchical data. Based on the zoning environmental deviation classification data and the real-time activity status data of chicken flocks in each secondary micro-zone, the corresponding zoning control mode data for each secondary micro-zone is determined.

[0062] In one embodiment of this application, the partition control module 25 is specifically used to perform validity verification processing on the real-time activity status data of the chicken flock to obtain valid chicken flock status data. Based on the zoning environmental deviation classification data, effective flock status data, and flock density differences in each secondary micro-zone, the corresponding zoning control mode data for each secondary micro-zone are determined.

[0063] In one embodiment of this application, when performing environmental actions based on the zoning control mode data, the negative pressure of each secondary micro-zone is monitored and controlled; the chicken house environmental control system 20 further includes: a negative pressure control module, used to acquire real-time negative pressure data of each secondary micro-zone, and determine the target negative pressure data corresponding to each secondary micro-zone based on the negative pressure threshold corresponding to the chicken flock growth stage, the ventilation status of the secondary micro-zone and the chicken flock density; The real-time negative pressure data is compared with the target negative pressure data to obtain the negative pressure deviation data; Based on the negative pressure deviation data, adjust the operating parameters of the ventilation actuators in the corresponding secondary micro-zones.

[0064] Each module in the aforementioned chicken coop environmental control system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0065] In some embodiments, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores primary partition data, secondary partition data, and partition control mode data. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a chicken coop environment control method.

[0066] In some embodiments, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 5As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a chicken coop environment control method. The display unit of the computer device is used to form a visually visible image. It can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0067] Those skilled in the art will understand that Figure 4 , Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0068] In some embodiments, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the chicken coop environment control method described above.

[0069] In some embodiments, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the chicken coop environment control method described above.

[0070] In some embodiments, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the chicken coop environment control method described above.

[0071] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0072] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logic devices, etc., and are not limited to these.

[0073] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0074] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for controlling the environment of a chicken coop, characterized in that, include: The physical spatial structure data of the chicken coop is divided into regions to obtain multiple primary partition data and multiple secondary partition data; Based on the chicken flock density, the data of each secondary partition is divided into micro-regions to obtain multiple secondary micro-partition data; The multiple primary partition data include passageway data, and the multiple secondary partition data include aquaculture area data; Based on the data of the chicken flock's growth stage, preset environmental parameter thresholds are matched to the data of each secondary micro-region to obtain the basic environmental control data of each secondary micro-region. Based on the external environment data of the chicken coop, the basic environmental control data of the partition is corrected to determine the target environmental control data of each secondary micro-partition. Extract the partition environment data from each secondary micro-partition data, and compare and calculate the partition environment deviation data of each secondary micro-partition based on the partition environment data and the partition target environment control data; Based on the partition environment deviation data, the partition control mode data corresponding to each secondary micro-partition is determined.

2. The chicken coop environment control method as described in claim 1, characterized in that, The process of correcting the basic environmental control data of the zones based on the external environmental data of the chicken coop, and determining the target environmental control data for each secondary micro-zone, includes: The raw signals collected by the outdoor temperature and humidity sensor of the chicken house are acquired, and the raw signals are subjected to analog-to-digital conversion and filtering to obtain standardized external environmental data. Based on the standardized external environment data, an environmental correction coefficient is determined, and the correction coefficient is calculated with the basic environmental control data of the partition to obtain a correction reference value; Different position correction weights are assigned based on the position differences of each secondary micro-partition. The position correction weights are then weighted and calculated with the correction benchmark value to obtain the target correction value. The partition basic environment control data and the target correction value are superimposed to obtain the partition target environment control data corresponding to each secondary micro-partition.

3. The chicken coop environment control method as described in claim 2, characterized in that, The determination of the environmental correction coefficient based on the standardized external environment data includes: The standardized external environment data is smoothed over time to obtain the average outdoor environment data. The difference between the average outdoor environmental data and the environmental tolerance threshold corresponding to the growth stage of the chicken flock is calculated to obtain the environmental deviation benchmark value. Based on the ventilation status of each secondary micro-zone, the ventilation adjustment coefficient corresponding to each secondary micro-zone is assigned. The environmental deviation benchmark value is weighted and calculated with the ventilation adjustment coefficient. The environmental correction coefficients corresponding to each secondary micro-partition are obtained.

4. The chicken coop environment control method as described in claim 3, characterized in that, The step of smoothing the standardized external environment data over time to obtain the average outdoor environment data includes: Construct a sliding time window; The average value of the standardized external environment data within the sliding time window is calculated to obtain the average outdoor environment data.

5. The chicken coop environment control method as described in claim 1, characterized in that, The step of determining the partition control mode data corresponding to each secondary micro-partition based on the partition environment deviation data includes: The partitioned environmental deviation data is graded to obtain partitioned environmental deviation graded data; Based on the zoning environmental deviation classification data and the real-time activity status data of chicken flocks in each secondary micro-zone, the zoning control mode data corresponding to each secondary micro-zone is determined.

6. The chicken coop environment control method as described in claim 5, characterized in that, The determination of the partition control mode data corresponding to each secondary micro-partition based on the partition environmental deviation classification data and the real-time activity status data of the chicken flock in each secondary micro-partition includes: The real-time activity status data of the chicken flock is validated to obtain valid chicken flock status data; Based on the zoning environmental deviation grading data, the effective flock status data, and the flock density differences in each secondary micro-zone, the zoning control mode data corresponding to each secondary micro-zone is determined.

7. The chicken coop environment control method as described in claim 1, characterized in that, When performing environmental actions based on the partition control mode data, the negative pressure of each secondary micro-partition is monitored and controlled; The monitoring and regulation of negative pressure in each secondary micro-zone includes: Real-time negative pressure data of each secondary micro-zone is obtained. Based on the negative pressure threshold corresponding to the chicken flock growth stage, the ventilation status of the secondary micro-zone, and the chicken flock density, the target negative pressure data corresponding to each secondary micro-zone is determined. The real-time negative pressure data is compared with the target negative pressure data to obtain negative pressure deviation data; Based on the negative pressure deviation data, adjust the operating parameters of the ventilation actuators in the corresponding secondary micro-zones.

8. A chicken coop environment control system, characterized in that, include: The region division module is used to divide the physical spatial structure data of the chicken house into regions, resulting in multiple primary partition data and multiple secondary partition data. Based on the chicken flock density, the data of each secondary partition is divided into micro-regions to obtain multiple secondary micro-partition data; The multiple primary partition data include passageway data, and the multiple secondary partition data include aquaculture area data; The partition basic environment matching module is used to match preset environmental parameter thresholds to the data of each secondary micro-partition based on the data of the chicken flock growth stage, so as to obtain the partition basic environment control data corresponding to each secondary micro-partition. The partition target environment correction module is used to correct the partition basic environment control data based on the chicken house external environment data, and determine the partition target environment control data corresponding to each secondary micro-partition; The partition environment deviation calculation module is used to extract partition environment data from each secondary micro-partition data, and compare the partition environment data with the partition target environment control data to determine the partition environment deviation data of each secondary micro-partition. The partition control module is used to determine the partition control mode data corresponding to each secondary micro-partition based on the partition environment deviation data.

9. A computer device, characterized in that, The computer device includes a processor and a memory; The memory is used to store computer programs; The processor is used to execute the chicken house environment control method according to any one of claims 1-7 according to the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program, which, when executed by a computer device, implements the chicken coop environment control method according to any one of claims 1-7.

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