Greenhouse environment control method and greenhouse control system based on AI algorithm

Abstract

The application discloses a greenhouse environment control method and a greenhouse control system based on an AI algorithm, which is used for improving the foresight of greenhouse environment regulation. The method comprises the following steps: acquiring current environment state data in a greenhouse, and judging whether the greenhouse environment meets a regulation trigger condition based on the current environment state data; in the case that the greenhouse environment meets the regulation trigger condition, acquiring historical environment state data associated with the current environment state data; performing prediction processing on the environment state time series data to obtain an environment regulation target corresponding to a next control period; determining a control amount of an environment regulation device according to a deviation between the environment regulation target and the current environment state data, and generating a device regulation instruction; controlling the environment regulation device to execute the device regulation instruction, acquiring environment state feedback data after the environment regulation device executes the device regulation instruction, and determining whether to continue the environment regulation according to the environment state feedback data.

Description

Technical Field

[0001] This application relates to the field of greenhouse control technology, and in particular to a greenhouse environment control method and greenhouse control system based on AI algorithms. Background Technology

[0002] Greenhouse cultivation is an important production method in facility agriculture, providing adjustable environmental conditions for crop growth within a relatively enclosed space. The greenhouse environment typically involves multiple environmental factors such as temperature, humidity, light, and carbon dioxide concentration. Changes in these environmental conditions directly affect crop growth quality and production stability. Therefore, timely and accurate control of the greenhouse environment is a crucial aspect of improving greenhouse cultivation management.

[0003] Current greenhouse environment control methods typically rely on manual experience or fixed threshold control. In fixed threshold control, the control system usually adjusts the corresponding environmental regulation equipment only after detecting that the current environmental parameters exceed the preset range. While this method can achieve a certain degree of automatic control of the greenhouse environment, its regulation is mainly based on the current environmental conditions, lacking comprehensive utilization of historical environmental changes, and thus failing to accurately reflect the changing trends of the greenhouse environment.

[0004] Because greenhouse environments are constantly changing, environmental data at a single moment often only represents the current state and cannot fully reflect the direction and magnitude of changes in environmental parameters over a period of time. If adjustments are only made after environmental parameters have exceeded thresholds, it can easily lead to a lag in greenhouse environmental control response, making it difficult for environmental regulation equipment to adjust the greenhouse environment to a suitable state in a timely manner. This is especially true when external climate changes rapidly or when there are significant fluctuations in the internal greenhouse environment, making it even more difficult for traditional control methods to determine control targets in advance based on environmental change trends.

[0005] Therefore, existing greenhouse environmental control methods suffer from insufficient foresight in regulation, making it difficult to determine corresponding environmental regulation targets in advance based on the temporal changes in environmental conditions, thus affecting the timeliness and adaptability of greenhouse environmental regulation. Summary of the Invention

[0006] This application provides a greenhouse environment control method and greenhouse control system based on AI algorithms, which can improve the foresight of greenhouse environment regulation.

[0007] The first aspect of this application provides a greenhouse environment control method based on AI algorithms, applied to a greenhouse control system, comprising:

[0008] Acquire the current environmental status data inside the greenhouse, and determine whether the greenhouse environment meets the control triggering conditions based on the current environmental status data; When the greenhouse environment meets the aforementioned control triggering conditions, historical environmental state data associated with the current environmental state data is acquired, and environmental state time series data is constructed based on the current environmental state data and the historical environmental state data. The environmental state time series data is subjected to predictive processing to obtain the environmental regulation target corresponding to the next control cycle; Based on the deviation between the environmental control target and the current environmental state data, the control quantity of the environmental control equipment is determined, and the equipment control command is generated based on the control quantity. The system controls the environmental control device to execute the device control command, and obtains environmental status feedback data after the environmental control device executes the device control command. Based on the environmental status feedback data, it determines whether to continue environmental control.

[0009] Optionally, determining whether the greenhouse environment meets the control triggering conditions based on the current environmental state data includes: At least one environmental state parameter in the current environmental state data is compared with the corresponding control threshold range; wherein the control threshold range is determined according to the current growth stage of the crops in the greenhouse. When at least one environmental state parameter is lower than the lower limit of the corresponding control threshold range or higher than the upper limit of the corresponding control threshold range, the greenhouse environment is determined to meet the control triggering condition.

[0010] Optionally, the current environmental status data and the historical environmental status data are acquired at a set acquisition frequency, which is determined based on the growth stage and / or environmental fluctuation sensitivity.

[0011] Optionally, constructing environmental state time-series data based on the current environmental state data and the historical environmental state data includes: The current environmental status data and the historical environmental status data are subjected to abnormal data removal and / or data fusion processing. The processed current environmental state data and historical environmental state data are arranged in chronological order of collection time to obtain the environmental state time series data.

[0012] Optionally, the step of predicting the environmental state time-series data to obtain the environmental regulation target corresponding to the next control cycle includes: The environmental state time series data is input into the trained time series prediction model to obtain the target setpoint value of at least one environmental state parameter in the next control cycle. The target set value is used as the environmental control target.

[0013] Optionally, determining the control quantity of the environmental control equipment based on the deviation between the environmental control target and the current environmental state data includes: Determine the parameter deviation between the target set value and the corresponding environmental state parameter in the current environmental state data; The parameter deviation is converted into a control quantity for the environmental control device using a control quantity generation algorithm.

[0014] Optionally, determining whether to continue environmental control based on the environmental status feedback data includes: The environmental status feedback data is compared with the corresponding control threshold range; When the environmental status feedback data still exceeds the corresponding control threshold range, environmental control continues based on the environmental status feedback data. When the environmental status feedback data returns to the corresponding control threshold range, the current control process ends. An alarm message is generated when the environmental status feedback data continuously exceeds the corresponding control threshold range, or when the environmental status feedback data reaches a preset alarm threshold.

[0015] A second aspect of this application provides a greenhouse control system for implementing the method of the first aspect and any possible implementation thereof, comprising: The first acquisition unit is used to acquire the current environmental status data inside the greenhouse, and determine whether the greenhouse environment meets the control triggering conditions based on the current environmental status data. The second acquisition unit is used to acquire historical environmental state data associated with the current environmental state data when the greenhouse environment meets the control triggering conditions, and to construct environmental state time series data based on the current environmental state data and the historical environmental state data. The prediction unit is used to perform prediction processing on the environmental state time series data to obtain the environmental regulation target corresponding to the next control cycle. The determining unit is used to determine the control quantity of the environmental control equipment based on the deviation between the environmental control target and the current environmental state data, and to generate equipment control instructions based on the control quantity; The control unit is used to control the environmental control equipment to execute the equipment control command, and to acquire environmental status feedback data after the environmental control equipment executes the equipment control command, and to determine whether to continue environmental control based on the environmental status feedback data.

[0016] A third aspect of this application provides an electronic device, comprising: Processor, memory, input / output units, and bus; The processor is connected to the memory, the input / output unit, and the bus; The memory stores a program, and the processor calls the program to execute the method of the first aspect and any possible implementation of the first aspect.

[0017] The fourth aspect of this application provides a computer-readable storage medium storing a program that, when executed on a computer, causes the computer to perform the methods of the first aspect and any possible implementation thereof.

[0018] As can be seen from the above technical solutions, this application has the following advantages: In this application, the greenhouse control system, when the current environmental state data meets the control triggering conditions, acquires historical environmental state data associated with the current environmental state data and constructs environmental state time-series data. This time-series data is then processed for prediction to obtain the environmental control target for the next control cycle. This allows greenhouse environmental control to no longer rely solely on the current threshold judgment, but to determine subsequent control targets by combining historical trends in environmental state changes. This reduces the problems of response lag and static control targets in traditional greenhouse environmental control, improving the foresight and dynamic adaptability of greenhouse environmental control. Simultaneously, the greenhouse control system determines the control quantity of the environmental regulation equipment based on the deviation between the environmental control target and the current environmental state data. After the environmental regulation equipment executes the equipment control command, it determines whether to continue environmental control based on environmental state feedback data. This forms a continuous, interconnected closed-loop control process involving environmental monitoring, target prediction, equipment adjustment, and feedback judgment, improving the accuracy and operational stability of greenhouse environmental control. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0020] Figure 1 This is a flowchart illustrating one embodiment of the greenhouse environment control method based on AI algorithms in this application; Figure 2 This is a flowchart illustrating a sub-implementation of the greenhouse environment control method using the AI ​​algorithm in this application. Figure 3 This is a flowchart illustrating another sub-implementation of the greenhouse environment control method using AI algorithms in this application; Figure 4 This is a flowchart illustrating another sub-implementation of the greenhouse environment control method using AI algorithms in this application; Figure 5 This is a flowchart illustrating another sub-implementation of the greenhouse environment control method using AI algorithms in this application; Figure 6 This is a flowchart illustrating another sub-implementation of the greenhouse environment control method using AI algorithms in this application; Figure 7 This is a schematic diagram of the structure of one embodiment of the greenhouse control system in this application; Figure 8 This is a schematic diagram of the structure of one embodiment of the electronic device in this application. Detailed Implementation

[0021] This application provides a greenhouse environment control method and greenhouse control system based on AI algorithms to improve the foresight of greenhouse environment regulation.

[0022] The method described in this application can be applied to servers, terminals, or other devices with logical processing capabilities; therefore, this application does not limit its application. For ease of description, the following description uses a server as the executing entity.

[0023] The embodiments of this application will now be described with reference to the accompanying drawings.

[0024] Please see Figure 1 , Figure 1 An embodiment of the greenhouse environment control method provided in this application, which can be applied to a greenhouse control system, includes: 101. Obtain the current environmental status data inside the greenhouse, and determine whether the greenhouse environment meets the control triggering conditions based on the current environmental status data; The greenhouse control system acquires current environmental status data within the greenhouse. This data characterizes the greenhouse environment at the current moment or within the current data collection period and may include at least one parameter related to the greenhouse environment. After acquiring the current environmental status data, the control system matches it with preset control trigger conditions to determine whether the current greenhouse environment requires the activation of the control process.

[0025] The control trigger conditions can be preset according to the needs of greenhouse environmental management. When the current environmental status data meets the control trigger conditions, the greenhouse control system determines that the greenhouse environment needs to be controlled; when the current environmental status data does not meet the control trigger conditions, the greenhouse control system can continue to acquire the current environmental status data inside the greenhouse to maintain monitoring of the greenhouse environment.

[0026] 102. When the greenhouse environment meets the control triggering conditions, acquire historical environmental state data associated with the current environmental state data, and construct environmental state time series data based on the current environmental state data and historical environmental state data; When the greenhouse control system determines that the greenhouse environment meets the control trigger conditions, it acquires historical environmental state data associated with the current environmental state data. This historical environmental state data can be environmental state data generated prior to the current environmental state data, and it has a temporal, regional, or parameter type correlation with the current environmental state data.

[0027] The greenhouse control system constructs time-series environmental state data based on current and historical environmental state data. This time-series data includes multiple environmental state data points arranged chronologically, allowing the current and historical environmental state data to form a continuous or near-continuous sequence of environmental state changes. This time-series environmental state data is used to characterize the state changes of the greenhouse environment within a certain time range.

[0028] 103. Perform predictive processing on environmental state time series data to obtain environmental control targets corresponding to the next control cycle; The greenhouse control system performs predictive processing on time-series environmental data to obtain environmental control targets for the next control cycle. These targets represent the desired state that the greenhouse environment needs to achieve or approach within the next control cycle.

[0029] The predictive processing can be performed based on changes in environmental conditions reflected in time-series environmental data. The greenhouse control system can process the time-series environmental data based on a preset predictive method to obtain environmental control targets corresponding to the next control cycle. Environmental control targets may include target values ​​or target ranges corresponding to at least one environmental state parameter.

[0030] 104. Based on the deviation between the environmental control target and the current environmental status data, determine the control quantity of the environmental control equipment, and generate equipment control instructions based on the control quantity; The greenhouse control system determines the control parameters of the environmental regulation equipment based on the deviation between the environmental control target and the current environmental state data. This deviation represents the difference between the current environmental state and the environmental control target for the next control cycle. The greenhouse control system can then determine the degree of regulation that the environmental regulation equipment needs to perform based on this difference.

[0031] After determining the control variables, the greenhouse control system generates equipment control commands based on these variables. These commands instruct the environmental control equipment to perform adjustment actions according to the corresponding control variables. The control commands may include control parameters related to the adjustment actions performed by the environmental control equipment, enabling the equipment to operate according to the commands.

[0032] 105. Control the environmental control equipment to execute equipment control commands, and obtain environmental status feedback data after the environmental control equipment executes the equipment control commands, and determine whether to continue environmental control based on the environmental status feedback data.

[0033] The greenhouse control system controls the environmental regulation equipment to execute equipment control commands, causing the equipment to adjust the greenhouse environment according to these commands. After the environmental regulation equipment executes the control commands, the greenhouse control system acquires environmental status feedback data. This feedback data characterizes the greenhouse environmental state after the environmental regulation equipment has executed the control commands.

[0034] The greenhouse control system determines whether to continue environmental regulation based on environmental status feedback data. When the environmental status feedback data indicates that the greenhouse environment still needs regulation, the greenhouse control system can continue environmental regulation; when the environmental status feedback data indicates that the greenhouse environment does not need further regulation, the greenhouse control system can terminate the current regulation process or continue monitoring the greenhouse environment.

[0035] In this embodiment, when the current environmental state data meets the control triggering conditions, the greenhouse control system acquires historical environmental state data associated with the current environmental state data and constructs environmental state time-series data. This time-series data is then used for predictive processing to obtain the environmental control target for the next control cycle. This allows greenhouse environmental control to no longer rely solely on the current threshold judgment, but rather to determine subsequent control targets by combining historical trends in environmental state changes. This reduces the problems of response lag and static control targets in traditional greenhouse environmental control, improving the foresight and dynamic adaptability of greenhouse environmental control. Simultaneously, the greenhouse control system determines the control quantity of the environmental regulation equipment based on the deviation between the environmental control target and the current environmental state data. After the environmental regulation equipment executes the equipment control command, it determines whether to continue environmental control based on environmental state feedback data. This forms a continuous, interconnected closed-loop control process involving environmental monitoring, target prediction, equipment adjustment, and feedback judgment, improving the accuracy and operational stability of greenhouse environmental control.

[0036] Please see Figure 2 In some embodiments of this application, step 101 in the above embodiments, which determines whether the greenhouse environment meets the control triggering conditions based on the current environmental state data, may include the following steps: 201. Compare at least one environmental state parameter in the current environmental state data with the corresponding control threshold range; After acquiring current environmental status data, the greenhouse control system can determine at least one environmental status parameter from the data and obtain the corresponding control threshold range for that parameter. The control threshold range represents the permissible or suitable range for the environmental status parameter in greenhouse environmental control and management. The greenhouse control system compares the current value of the environmental status parameter with the corresponding control threshold range to determine whether the parameter falls within that range.

[0037] Different environmental state parameters can correspond to different control threshold ranges. When the current environmental state data includes multiple environmental state parameters, the greenhouse control system can compare each environmental state parameter with its corresponding control threshold range to obtain the positional relationship of each environmental state parameter relative to its corresponding control threshold range.

[0038] In this embodiment, the greenhouse control system compares at least one environmental state parameter in the current environmental state data with the corresponding control threshold range, so that whether the greenhouse environment needs to be controlled can be determined by the correspondence between the environmental state parameter and the control threshold range, avoiding the need to make a unified judgment on different environmental state parameters based on a single fixed judgment condition, and improving the pertinence of the control trigger judgment.

[0039] 202. When at least one environmental state parameter is lower than the lower limit of the corresponding control threshold range or higher than the upper limit of the corresponding control threshold range, the greenhouse environment is determined to meet the control triggering condition. The greenhouse control system determines whether an environmental state parameter exceeds the corresponding control threshold range by comparing the environmental state parameters with the corresponding control threshold range. When at least one environmental state parameter is below the lower limit of the corresponding control threshold range or above the upper limit of the corresponding control threshold range, it indicates that at least one environmental state parameter in the current greenhouse environment deviates from the corresponding allowable or suitable range, and the greenhouse control system determines that the greenhouse environment meets the control triggering conditions.

[0040] When the current environmental status data includes multiple environmental status parameters, the greenhouse environment can be determined to meet the control triggering conditions as long as at least one of the environmental status parameters is below the lower limit of its corresponding control threshold range or above the upper limit of its corresponding control threshold range. If all environmental status parameters are within their corresponding control threshold ranges, the greenhouse control system can determine that the greenhouse environment does not meet the control triggering conditions.

[0041] In this embodiment, when at least one environmental state parameter is lower than the lower limit of the corresponding control threshold range or higher than the upper limit of the corresponding control threshold range, the greenhouse control system determines that the greenhouse environment meets the control triggering conditions, so that the control triggering judgment can cover two types of abnormal situations: low and high environmental state parameters, thereby improving the completeness of the greenhouse environment control start judgment.

[0042] The current environmental status data and historical environmental status data are acquired according to a set collection frequency, which is determined based on the growth stage and / or sensitivity to environmental fluctuations.

[0043] When acquiring current and historical environmental data, the greenhouse control system can collect data at a set frequency. The set frequency can be determined based on the crop's growth stage, the greenhouse environment's sensitivity to fluctuations, or both.

[0044] The growth stage represents the crop's growth process within the greenhouse, and different growth stages may have different response requirements to changes in environmental conditions. Environmental fluctuation sensitivity represents the degree to which the greenhouse environment is sensitive to changes in external conditions or internal states. When the growth stage is highly sensitive to changes in environmental conditions or has a high sensitivity to environmental fluctuations, a relatively high sampling frequency can be used; conversely, when the growth stage is less sensitive to changes in environmental conditions or has a low sensitivity to environmental fluctuations, a relatively low sampling frequency can be used.

[0045] In this embodiment, current environmental status data and historical environmental status data are acquired at a set acquisition frequency. The set acquisition frequency is determined based on the growth stage and / or sensitivity to environmental fluctuations, so that the acquisition frequency of environmental status data can match the crop growth needs or environmental change characteristics. This reduces the problem that a fixed acquisition frequency cannot balance data timeliness and acquisition resource consumption, and improves the adaptability of greenhouse environmental status data acquisition.

[0046] Please see Figure 3 In some embodiments of this application, step 103 in the above embodiments, which constructs environmental state time-series data based on current environmental state data and historical environmental state data, may include the following steps: 301. Perform abnormal data removal and / or data fusion processing on current environmental status data and historical environmental status data; After acquiring current and historical environmental status data, the greenhouse control system can perform anomaly removal processing on both sets of data. Anomalies can be environmental status data that does not meet preset data validity requirements, such as data with abnormal format, missing data, data exceeding a preset valid range, or data with abnormal deviations from adjacent data collection. The greenhouse control system can identify anomalies based on preset data validity requirements and remove them from the current or historical environmental status data.

[0047] The greenhouse control system can also perform data fusion processing on current and historical environmental status data. Data fusion processing integrates data from the same acquisition time, the same environmental state parameter, or the same environmental object, giving the processed environmental status data a unified data representation format. After data fusion processing, current and historical environmental status data can participate in the construction of environmental status time-series data according to a consistent data structure.

[0048] 302. Arrange the processed current environmental status data and historical environmental status data in the order of collection time to obtain environmental status time series data.

[0049] After completing the abnormal data removal and / or data fusion processing, the greenhouse control system can sort the processed current environmental status data and historical environmental status data according to their corresponding acquisition times. During sorting, historical environmental status data can be arranged in chronological order of acquisition time, and current environmental status data can be added to the sorting result as the environmental status data corresponding to the current acquisition time.

[0050] After being arranged, the processed current environmental state data and historical environmental state data form a data sequence distributed in chronological order of collection time. This data sequence is the environmental state time series data. In the environmental state time series data, there is a clear temporal order relationship between the various environmental state data, which can characterize the process of changes in the greenhouse environmental state over time.

[0051] In this embodiment, the greenhouse control system performs anomaly removal and / or data fusion processing on the current and historical environmental state data. This reduces interference from anomaly data in the environmental state data participating in the time-series data construction and forms a more consistent data representation, improving the reliability of the environmental state time-series data. The greenhouse control system arranges the processed current and historical environmental state data according to the acquisition time sequence to obtain environmental state time-series data, establishing a temporal correlation between the current and historical environmental state data and improving the orderly representation of the greenhouse environmental state change process.

[0052] Please see Figure 4 In some embodiments of this application, step 103 in the above embodiments, which performs predictive processing on environmental state time-series data to obtain the environmental regulation target corresponding to the next control cycle, may include the following steps: 401. Input the environmental state time series data into the trained time series prediction model to obtain the target setpoint value of at least one environmental state parameter in the next control cycle. The greenhouse control system can input time-series environmental state data into a trained time-series prediction model. The trained model processes the environmental state data with temporal relationships and outputs a prediction result corresponding to the next control cycle. This prediction result may include a target setpoint for at least one environmental state parameter within the next control cycle.

[0053] The environmental state time series data includes environmental state data arranged in chronological order of collection time. The trained time series prediction model can determine the target setpoints for the corresponding environmental state parameters in the next control cycle based on the environmental state changes reflected in the environmental state time series data. The target setpoints represent the set state that the environmental state parameters need to reach or approach in the next control cycle.

[0054] 402. Set the target value as the environmental control target.

[0055] After obtaining the target setpoint for at least one environmental state parameter for the next control cycle, the greenhouse control system can use that target setpoint as the environmental control target. The environmental control target represents the target state that the greenhouse environment needs to reach or approach in the next control cycle.

[0056] When the target setpoint includes a target setpoint for an environmental state parameter, the greenhouse control system can use that target setpoint as the corresponding environmental control target. When the target setpoint includes target setpoints for multiple environmental state parameters, the greenhouse control system can use the target setpoints of multiple environmental state parameters together as the environmental control target, so that the environmental control target can correspond to one or more environmental state parameters.

[0057] In this embodiment, the greenhouse control system inputs environmental state time-series data into a trained time-series prediction model to obtain target setpoints for at least one environmental state parameter in the next control cycle. This allows the target setpoints to be determined based on the temporal changes in the environmental state time-series data, reducing the lag caused by determining the target state solely based on current data and improving the adaptability of the target setpoint determination for the next control cycle. The greenhouse control system uses the target setpoints as environmental control targets, enabling the predicted target setpoints for the next control cycle to be directly used to characterize the control target state, reducing uncertainty in the target transition process and improving the clarity and consistency of the environmental control target determination process.

[0058] Please see Figure 5 In some embodiments of this application, step 104 in the above embodiments, which determines the control quantity of the environmental control equipment based on the deviation between the environmental control target and the current environmental state data, may include the following steps: 501. Determine the parameter deviation between the target setpoint and the corresponding environmental state parameter in the current environmental state data; After obtaining the environmental control target, the greenhouse control system can determine the environmental state parameters corresponding to the target setpoint based on the target setpoint contained in the environmental control target. The greenhouse control system determines the environmental state parameters corresponding to the target setpoint from the current environmental state data, and calculates the difference between the target setpoint and the corresponding environmental state parameters in the current environmental state data to obtain the parameter deviation.

[0059] Parameter deviation is used to represent the degree of deviation between the target setpoint and the current environmental state. Parameter deviation can reflect whether the current value of the corresponding environmental state parameter is higher or lower than the target setpoint. When the environmental control target includes multiple target setpoints, the greenhouse control system can determine the parameter deviation between each target setpoint and the corresponding environmental state parameter in the current environmental state data.

[0060] 502. Use a control quantity generation algorithm to convert parameter deviations into control quantities for environmental control equipment.

[0061] After determining the parameter deviations, the greenhouse control system can use a control quantity generation algorithm to process these deviations and convert them into control quantities for the environmental regulation equipment. This algorithm establishes a correspondence between parameter deviations and the control quantities of the environmental regulation equipment, allowing different magnitudes or directions of parameter deviations to correspond to different control quantities.

[0062] In this context, the control quantity can be used to represent the degree of adjustment of environmental regulation equipment. The greenhouse control system can input parameter deviations into the control quantity generation algorithm, which then outputs the control quantity corresponding to the parameter deviations. When multiple parameter deviations exist, the greenhouse control system can either use the control quantity generation algorithm to process each deviation separately, or perform comprehensive processing on multiple deviations to obtain the control quantity for the environmental regulation equipment.

[0063] In this embodiment, the greenhouse control system determines the parameter deviation between the target setpoint and the corresponding environmental state parameters in the current environmental state data. This allows the determination of control quantities for the environmental regulation equipment to be based on the actual difference between the target state and the current state, improving the matching between the control quantity determination process and the actual state of the greenhouse environment. The greenhouse control system uses a control quantity generation algorithm to convert the parameter deviation into control quantities for the environmental regulation equipment. This enables the control quantities to be quantified and determined based on the parameter deviation, reducing the subjectivity caused by manually setting control quantities and improving the accuracy of the control quantity generation for the environmental regulation equipment.

[0064] Please see Figure 6 In some embodiments of this application, step 105 in the above embodiments, which determines whether to continue environmental regulation based on environmental status feedback data, may include the following steps: 601. Compare the environmental status feedback data with the corresponding control threshold range; After acquiring environmental status feedback data, the greenhouse control system can determine the environmental status parameters contained in the feedback data and obtain the corresponding control threshold range. The greenhouse control system then compares the environmental status feedback data with the corresponding control threshold range to determine whether the greenhouse environment is within the corresponding control threshold range after the environmental regulation equipment executes its control commands.

[0065] When the environmental status feedback data includes multiple environmental status parameters, the greenhouse control system can compare the feedback data of each environmental status parameter with its corresponding control threshold range to obtain a comparison result of each environmental status parameter relative to its corresponding control threshold range. This comparison result can be used to characterize whether the environmental status feedback data still deviates from the corresponding control threshold range.

[0066] 602. When the environmental status feedback data still exceeds the corresponding control threshold range, continue to carry out environmental control based on the environmental status feedback data; The greenhouse control system compares the environmental status feedback data with the corresponding control threshold range to determine whether the environmental status feedback data still exceeds the corresponding control threshold range. When the environmental status feedback data is lower than the lower limit of the corresponding control threshold range or higher than the upper limit of the corresponding control threshold range, the greenhouse control system determines that the environmental status feedback data still exceeds the corresponding control threshold range.

[0067] When the environmental status feedback data still exceeds the corresponding control threshold range, the greenhouse control system continues to perform environmental control based on the environmental status feedback data. At this time, the environmental status feedback data can serve as the basis for continued control, enabling the greenhouse control system to continue to execute control decisions based on the actual environmental status after control.

[0068] 603. When the environmental status feedback data returns to the corresponding control threshold range, the current control process ends; The greenhouse control system determines whether the environmental status feedback data has returned to the corresponding control threshold range based on a comparison between the environmental status feedback data and the corresponding control threshold range. When the environmental status feedback data is not lower than the lower limit of the corresponding control threshold range and not higher than the upper limit of the corresponding control threshold range, the greenhouse control system determines that the environmental status feedback data has returned to the corresponding control threshold range.

[0069] When the environmental status feedback data returns to the corresponding control threshold range, the greenhouse control system ends the current control process. After the current control process ends, the greenhouse control system can maintain the acquisition of the greenhouse environmental status so that environmental control can be restarted when the greenhouse environment meets the control trigger conditions again.

[0070] 604. When the environmental status feedback data continuously exceeds the corresponding control threshold range, or when the environmental status feedback data reaches the preset alarm threshold, an alarm prompt message is generated.

[0071] The greenhouse control system can determine whether the environmental status feedback data continuously exceeds the corresponding control threshold range based on the comparison results between the environmental status feedback data and the corresponding control threshold range. Continuously exceeding the corresponding control threshold range can mean that the environmental status feedback data is below the lower limit of the corresponding control threshold range for multiple consecutive feedback cycles, or above the upper limit of the corresponding control threshold range for multiple consecutive feedback cycles.

[0072] The greenhouse control system can also determine whether the environmental status feedback data has reached a preset alarm threshold. The preset alarm threshold indicates the environmental state boundary that requires an alarm notification. When the environmental status feedback data continuously exceeds the corresponding control threshold range, or when the environmental status feedback data reaches the preset alarm threshold, the greenhouse control system generates an alarm notification. The alarm notification is used to indicate that there is an abnormal situation in the greenhouse environment that requires attention.

[0073] In this embodiment, the greenhouse control system compares the environmental status feedback data with the corresponding control threshold range, and determines whether to continue environmental control, terminate the current control process, or generate an alarm message based on the comparison result. This allows the environmental control process to continue, stop, or provide an anomaly warning based on the actual feedback status after control, avoiding premature termination of control when the environmental status still exceeds the control threshold range, and also avoiding unnecessary control after the environmental status has returned to the control threshold range. At the same time, generating an alarm message when the environmental status feedback data continuously exceeds the corresponding control threshold range or reaches the preset alarm threshold improves the ability to identify and warn of continuous abnormal environmental states, thereby improving the closed-loop nature, stability, and safety of the greenhouse environmental control process.

[0074] In the foregoing embodiments, the specific implementation process of the method provided in this application has been described in detail. It should be understood that, to implement the above method, this application also provides corresponding devices and computer-readable storage media, the technical concepts of which are consistent with the foregoing method embodiments, and both are used to implement all or part of the steps in the foregoing method. The technical solutions of the devices and computer-readable storage media involved in this application will be further described below in conjunction with specific embodiments.

[0075] Please see Figure 7 , Figure 7 One embodiment of the greenhouse control system provided in this application includes: The first acquisition unit 701 is used to acquire the current environmental status data inside the greenhouse and determine whether the greenhouse environment meets the control triggering conditions based on the current environmental status data. The second acquisition unit 702 is used to acquire historical environmental state data associated with the current environmental state data when the greenhouse environment meets the control triggering conditions, and to construct environmental state time series data based on the current environmental state data and the historical environmental state data. The prediction unit 703 is used to perform prediction processing on environmental state time series data to obtain the environmental regulation target corresponding to the next control cycle. The determining unit 704 is used to determine the control quantity of the environmental control equipment based on the deviation between the environmental control target and the current environmental state data, and to generate equipment control instructions based on the control quantity; The control unit 705 is used to control the environmental control equipment to execute equipment control commands, and to obtain environmental status feedback data after the environmental control equipment executes the equipment control commands, and to determine whether to continue environmental control based on the environmental status feedback data.

[0076] Please see Figure 8 , Figure 8 One embodiment of the electronic device provided in this application includes: Processor 801, memory 802, input / output unit 803, and bus 804; The processor 801 is connected to the memory 802, the input / output unit 803, and the bus 804; The memory 802 stores a program, which the processor 801 calls to execute. Figures 1 to 6 The steps in the illustrated embodiment.

[0077] In this embodiment, the function of processor 801 is the same as described above. Figures 1 to 6 The steps in the illustrated embodiments are the same and will not be repeated here.

[0078] This application also provides a computer-readable storage medium on which a program is stored. When the program is executed on a computer, it causes the computer to perform the aforementioned actions. Figures 1 to 6 The method in any possible implementation.

[0079] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0081] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0083] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it 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 all or part of the 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 to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A greenhouse environment control method based on AI algorithms, characterized in that, Applied to a greenhouse control system, the method includes: Acquire the current environmental status data inside the greenhouse, and determine whether the greenhouse environment meets the control triggering conditions based on the current environmental status data; When the greenhouse environment meets the aforementioned control triggering conditions, historical environmental state data associated with the current environmental state data is acquired, and environmental state time series data is constructed based on the current environmental state data and the historical environmental state data. The environmental state time series data is subjected to predictive processing to obtain the environmental regulation target corresponding to the next control cycle; Based on the deviation between the environmental control target and the current environmental state data, the control quantity of the environmental control equipment is determined, and the equipment control command is generated based on the control quantity. The system controls the environmental control device to execute the device control command, and obtains environmental status feedback data after the environmental control device executes the device control command. Based on the environmental status feedback data, it determines whether to continue environmental control.

2. The greenhouse environment control method according to claim 1, characterized in that, The step of determining whether the greenhouse environment meets the control triggering conditions based on the current environmental state data includes: At least one environmental state parameter in the current environmental state data is compared with the corresponding control threshold range; wherein the control threshold range is determined according to the current growth stage of the crops in the greenhouse. When at least one environmental state parameter is lower than the lower limit of the corresponding control threshold range or higher than the upper limit of the corresponding control threshold range, the greenhouse environment is determined to meet the control triggering condition.

3. The greenhouse environment control method according to claim 2, characterized in that, The current environmental status data and the historical environmental status data are acquired at a set acquisition frequency, which is determined based on the growth stage and / or environmental fluctuation sensitivity.

4. The greenhouse environment control method according to claim 1, characterized in that, The step of constructing environmental state time-series data based on the current environmental state data and the historical environmental state data includes: The current environmental status data and the historical environmental status data are subjected to abnormal data removal and / or data fusion processing. The processed current environmental state data and historical environmental state data are arranged in chronological order of collection time to obtain the environmental state time series data.

5. The greenhouse environment control method according to claim 4, characterized in that, The step of predicting and processing the environmental state time-series data to obtain the environmental regulation target corresponding to the next control cycle includes: The environmental state time series data is input into the trained time series prediction model to obtain the target setpoint value of at least one environmental state parameter in the next control cycle. The target set value is used as the environmental control target.

6. The greenhouse environment control method according to claim 5, characterized in that, The step of determining the control quantity of the environmental control equipment based on the deviation between the environmental control target and the current environmental state data includes: Determine the parameter deviation between the target set value and the corresponding environmental state parameter in the current environmental state data; The parameter deviation is converted into a control quantity for the environmental control device using a control quantity generation algorithm.

7. The greenhouse environment control method according to claim 2, characterized in that, The step of determining whether to continue environmental control based on the environmental status feedback data includes: The environmental status feedback data is compared with the corresponding control threshold range; When the environmental status feedback data still exceeds the corresponding control threshold range, environmental control continues based on the environmental status feedback data. When the environmental status feedback data returns to the corresponding control threshold range, the current control process ends. An alarm message is generated when the environmental status feedback data continuously exceeds the corresponding control threshold range, or when the environmental status feedback data reaches a preset alarm threshold.

8. A greenhouse control system, characterized in that, For implementing the method of any one of claims 1 to 7, the greenhouse control system comprises: The first acquisition unit is used to acquire the current environmental status data inside the greenhouse, and determine whether the greenhouse environment meets the control triggering conditions based on the current environmental status data. The second acquisition unit is used to acquire historical environmental state data associated with the current environmental state data when the greenhouse environment meets the control triggering conditions, and to construct environmental state time series data based on the current environmental state data and the historical environmental state data. The prediction unit is used to perform prediction processing on the environmental state time series data to obtain the environmental regulation target corresponding to the next control cycle. The determining unit is used to determine the control quantity of the environmental control equipment based on the deviation between the environmental control target and the current environmental state data, and to generate equipment control instructions based on the control quantity; The control unit is used to control the environmental control equipment to execute the equipment control command, and to acquire environmental status feedback data after the environmental control equipment executes the equipment control command, and to determine whether to continue environmental control based on the environmental status feedback data.

9. An electronic device, characterized in that, include: Processor, memory, input / output units, and bus; The processor is connected to the memory, the input / output unit, and the bus; The memory stores a program, and the processor calls the program to execute the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains a program that, when executed on a computer, causes the computer to perform the method as described in any one of claims 1 to 7.

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