Intelligent environment regulation and control system for facility agriculture

Abstract

The invention discloses a facility agriculture intelligent environment regulation and control system, and relates to the field of environment regulation and control, and the system comprises a track, an edge calculation device, a sensing device, and an environment control device. The track is suspended at the top of the facility agriculture building; the edge calculation device and the sensing device are connected through a rope, and the edge calculation device is suspended below the track; the environment control devices are placed at all positions of the facility agriculture building. The sensing device collects crop environment data and crop growth data of a target position; the edge computing device obtains the optimal growth environment of the growth stage of the crop at the target position by using an artificial intelligence algorithm according to the crop environment data and the crop growth vigor data, and forms a control command; and the environment control device regulates and controls the environment data according to the control command, so that the environment data of the target position reaches the optimal growth environment of the growth stage of the crops. The crop growth environment at any position can be regulated and controlled in real time, and the environment regulation and control efficiency and accuracy are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of environmental regulation, and in particular to an intelligent environmental regulation system for facility agriculture. BACKGROUND

[0002] The current facility agriculture environmental regulation technology generally includes an environmental monitoring module and an environmental control module. The environmental monitoring module obtains environmental data such as temperature, humidity, light, and carbon dioxide in the facility greenhouse in real time, uploads the environmental data to the environmental control module, and the environmental control module compares the environmental data with preset environmental parameters to control devices such as air conditioners and humidifiers, thereby adjusting the facility agriculture environment and ensuring that crops grow in the best environment. In an existing technology of the same type, an automatic environmental regulation system for Chinese herbal medicine planting obtains temperature, humidity, light intensity, soil pH value, and soil nutrient concentration data of the Chinese herbal medicine planting environment through an environmental quality evaluation module, obtains results by comparing entropy values, obtains regulation requirements based on the result evaluation by an environmental regulation requirement analysis module, adjusts environmental data parameters according to the regulation requirements by a planting mode optimization module, and finally adjusts real-time environmental parameters by an intelligent regulation module.

[0003] This technology uses a fixed measurement method to obtain environmental data, which has the disadvantages of small measurement range, high cost, low sensor life affected by ground humidity, and difficult maintenance.

[0004] There is a lack of a crop real-time growth state data acquisition unit. This technology relies on root system environmental changes to judge the crop growth state, which is an indirect means and has errors. The best growth environment required by crops in different growth stages is different, so the environmental control strategy needs to be adjusted according to the different growth stages of crops.

[0005] There is a lack of an edge computing intelligent control brain that adjusts the environmental control strategy according to the real-time growth state of crops. The current environmental control module compares whether the current environmental parameters and the preset parameters are consistent to regulate the crop growth environment. The preset parameters cannot be corrected in real time according to the current real growth state and growth stage of crops.

[0006] The environmental data acquisition device and the environmental regulation device are designed as two independent modules. After all data is acquired, it is input to the environmental regulation device for analysis, and then the next step of environmental regulation can be performed. Real-time environmental control at any location cannot be achieved. SUMMARY

[0007] The purpose of the present application is to provide an intelligent environmental regulation system for facility agriculture to achieve real-time regulation of the crop growth environment at any location to be in the best state and improve the efficiency and accuracy of environmental regulation.

[0008] To achieve the above purpose, the present application provides the following solutions: In a first aspect, the application provides an intelligent environment regulation system for facility agriculture, comprising: a track, an edge computing device, a sensing device, and an environment control device. The track is a I-shaped steel rail, and the track is suspended from the top of a facility agriculture building; the edge computing device and the sensing device are connected by a rope, the edge computing device is suspended below the track to drive the sensing device to run; and the environment control device is placed at various positions in the facility agriculture building. The sensing device is used to collect crop environment data and crop growth data at a target position in the facility agriculture building; the crop environment data includes temperature, humidity, carbon dioxide concentration, and light intensity. The edge computing device is used to derive the optimal growth environment for crops at the target position according to the crop environment data and the crop growth data, and form a control command by using an artificial intelligence algorithm. The environment control device is used to regulate the environment data at the target position in the facility agriculture building according to the control command, so that the environment data at the target position reaches the optimal growth environment for crops at the growth stage.

[0009] In an embodiment, the system further comprises a wireless charging device; and the wireless charging device is placed at a starting position of the track. The wireless charging device is used to charge the edge computing device.

[0010] In an embodiment, the wireless charging device comprises a first power supply module, a first control module, a first distance measuring module, a first wireless communication module, and a first transmitting coil module. The first power supply module is used to provide power to the first control module, the first distance measuring module, the first wireless communication module, and the first transmitting coil module. The first wireless communication module is used to receive a request charging command and a request power-off command after being fully charged from the edge computing device. The first distance measuring module is used to measure the distance between the wireless charging device and the edge computing device after the first wireless communication module receives the request charging command, and determine whether the edge computing device is at the starting position. The first control module is used to control the first transmitting coil module to charge or stop charging the edge computing device.

[0011] In an embodiment, the edge computing device comprises a first receiving coil, a second power supply module, an artificial intelligence module, a second distance measuring module, a second control module, a horizontal movement module, a vertical movement module, a second wireless communication module, and a second transmitting coil module. The first receiving coil is used to receive the magnetic signal emitted by the first transmitting coil module and convert it into electrical energy to charge the second power module; The second power module is used to supply power to the artificial intelligence module, the second ranging module, the second control module, the horizontal movement module, the vertical movement module, the second wireless communication module, and the second transmitting coil module; The artificial intelligence module is used to determine the optimal growth environment for the crop at the target location during its growth stage based on the crop environment data and the crop growth data, and to generate control commands. The second ranging module is used to measure the distance between the edge computing device and the sensing device, and to determine whether the sensing device is at the starting point; The horizontal movement module is used to drive the edge computing device to move the sensing device horizontally on the track; The vertical movement module is used to move the sensing device up and down. The second wireless communication module is used to send a request to charge command, a request to power off command, a command to acquire crop environment data and crop growth data to the sensing device, and the control command to the environmental control device; The second transmitting coil module is used to charge the sensing device; The second control module is used to schedule the first receiving coil, the second power supply module, the artificial intelligence module, the second ranging module, the horizontal movement module, the vertical movement module, the second wireless communication module, and the second transmitting coil module in real time.

[0012] In one embodiment, the sensing module includes: a second receiving coil, a third power supply module, a third control module, an environmental sensing module, a growth sensing module, and a third wireless communication module; The second receiving coil is used to receive the magnetic signal emitted by the second transmitting coil module and convert it into electrical energy to charge the third power supply module; The third power supply module is used to supply power to the third control module, the environmental sensing module, the growth sensing module and the third wireless communication module; The environmental sensing module is used to acquire crop environmental data at the target location within the facility agriculture building; The growth monitoring module is used to acquire crop growth data at the target location within the facility agriculture building; The third wireless communication module is used to upload the crop environment data and the crop growth data to the edge computing device; The third control module is used to schedule the second receiving coil, the third power supply module, the environmental sensing module, the growth sensing module, and the third wireless communication module in real time.

[0013] In one embodiment, the growth monitoring module includes an image sensor and a hyperspectral sensor.

[0014] In one embodiment, the environmental control device includes: a fourth power supply module, a fourth control module, an execution module, and a fourth wireless communication module; The fourth power supply module is used to supply power to the fourth control module, the execution module and the fourth wireless communication module; The execution module is used to adjust the environmental data of the target location within the facility agriculture building according to the control command, so that the environmental data of the target location reaches the optimal growth environment for the crop at its growth stage. The fourth wireless communication module is used to receive control commands from the edge computing device.

[0015] In one embodiment, the execution module includes a humidifier, an air conditioner, a carbon dioxide replenishment device, and a fan.

[0016] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides an intelligent environmental control system for facility agriculture, comprising: a track, an edge computing device, a sensing device, and an environmental control device; the track uses I-beam steel rails and is suspended from the top of the facility agriculture building; the edge computing device and the sensing device are connected by ropes, with the edge computing device suspended below the track to drive the sensing device; the environmental control device is placed at various locations within the facility agriculture building; the sensing device is used to collect crop environmental data and crop growth data at target locations within the facility agriculture building; the edge computing device is used to determine the optimal growth environment for the crop at the target location's growth stage based on the crop environmental data and crop growth data using artificial intelligence algorithms, and generates control commands; the environmental control device is used to regulate the environmental data at the target locations within the facility agriculture building according to the control commands, so that the environmental data at the target locations reaches the optimal growth environment for the crop at its growth stage. This application uses a track-mounted autonomous mobile monitoring device to acquire environmental and crop growth data at any location, solving the problems of small measurement range, high cost, short sensor life and difficult maintenance of fixed devices. By loading environmental sensors and crop growth monitoring sensors onto the monitoring device, it can directly acquire crop growth status and environmental data in real time. By loading edge computing devices and deploying environmental regulation artificial intelligence algorithms, it can achieve real-time regulation of the crop growth environment at any location to be at its optimal level. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments 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.

[0018] Figure 1 This is a schematic diagram of the structure of an intelligent environmental control system for facility agriculture provided in one embodiment of this application; Figure 2 This is a schematic diagram of the structure of a wireless charging device provided in an embodiment of this application; Figure 3 This is a schematic diagram of the composition structure of an edge computing device provided in an embodiment of this application; Figure 4 This is a schematic diagram of the composition structure of a sensing device provided in an embodiment of this application; Figure 5 This is a schematic diagram of the composition structure of a sensing device provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] This application provides an intelligent environmental control system for facility agriculture. It employs a track-mounted autonomous mobile monitoring device to acquire environmental and crop growth data at any location, solving problems associated with fixed systems such as small measurement range, high cost, short sensor lifespan, and difficult maintenance. By loading environmental and crop growth monitoring sensors onto the monitoring device, it achieves direct real-time acquisition of crop growth status and environmental data. An edge computing module is added, and an environmental control artificial intelligence algorithm is deployed to achieve real-time control of the crop growth environment at any location to ensure optimal conditions. A wireless charging module enables 24 / 7 unmanned intelligent control, solving the charging safety issues associated with physical charging interfaces.

[0022] In one exemplary embodiment, such as Figure 1 As shown, an intelligent environmental control system for facility agriculture is provided, including: a track, a wireless charging device, an edge computing device, a sensing device, and an environmental control device.

[0023] The track uses I-beam steel rails and is suspended from the top of the facility agriculture building. It can be designed into any shape according to the actual needs of environmental control data acquisition. The wireless charging device is placed at the starting position of the track. The edge computing device and the sensing device are connected by ropes. The edge computing device is suspended below the track and drives the sensing device to operate. The environmental control device is placed at various locations of the facility agriculture building according to environmental control needs.

[0024] The wireless charging device is used to charge the edge computing device.

[0025] As an alternative implementation method, such as Figure 2 As shown, the wireless charging device includes: a first power module, a first control module, a first ranging module, a first wireless communication module, and a first transmitting coil module.

[0026] The specific steps for determining whether an edge computing device is at the starting point are as follows: When the edge computing device sends a charging request command through the second wireless communication module, the wireless charging device receives it through the first wireless communication module and then activates the first ranging module to obtain the distance information between the wireless charging device and the edge computing device. If the distance is within a set range, such as within 5cm, it means that the edge computing device is located at the starting point. If it is greater than 5cm, it is considered that it is not at the starting point. This data is set according to the actual installation situation.

[0027] The first power module is used to provide power to the first control module, the first ranging module, the first wireless communication module and the first transmitting coil module.

[0028] The first wireless communication module is used to receive the charging request command and the power-off request command after the edge computing device is fully charged. The first wireless communication module is responsible for receiving the charging request and the power-off request after the edge computing device is fully charged, and transmitting them to the first control module.

[0029] The first ranging module is used to measure the distance between the wireless charging device and the edge computing device after the first wireless communication module receives a charging request command, and to determine whether the edge computing device is at the starting point. Under the control of the first control module, the first ranging module measures the distance between the wireless charging device and the edge computing device to determine whether the edge computing device is at the starting point.

[0030] The first control module controls the first transmitting coil module to charge or stop charging the edge computing device. The first transmitting coil module is responsible for charging the edge computing device under the control of the first control module. The first control module is responsible for real-time scheduling of the first ranging module, the first wireless communication module, and the first transmitting coil module to complete the various functions of the wireless charging device.

[0031] The function of the wireless charging device is to receive a charging request from the edge computing device through the first wireless communication module, and then use the first ranging module to obtain ranging information to determine whether the edge computing device is at the starting point. If it is, the device will supply power to the first transmitting coil module; otherwise, it will not supply power. This is the scheduling function.

[0032] The edge computing device is used to determine the optimal growth environment for the crop at the target location during its growth stage based on the crop environment data and the crop growth data, using artificial intelligence algorithms, and then generate control commands.

[0033] As an alternative implementation method, such as Figure 3 As shown, the edge computing device includes: a first receiving coil, a second power supply module, an artificial intelligence module, a second ranging module, a second control module, a horizontal movement module, a vertical movement module, a second wireless communication module, and a second transmitting coil module.

[0034] The specific steps for determining whether the sensing device is at the starting point are as follows: The sensing device sends a charging request command to the edge computing device through the third wireless communication module. After receiving the command through the second wireless communication module, the edge computing device obtains the distance between the edge computing device and the sensing device through the second ranging module. If the obtained data is within a set range, such as within 1cm, it means that the edge computing device is located at the starting point. If it is greater than 1cm, it is considered that the edge computing device is not at the starting point. This data is set according to the actual installation situation.

[0035] The first receiving coil is used to receive the magnetic signal emitted by the first transmitting coil module and convert it into electrical energy to charge the second power supply module.

[0036] The second power module is used to supply power to the artificial intelligence module, the second ranging module, the second control module, the horizontal movement module, the vertical movement module, the second wireless communication module, and the second transmitting coil module.

[0037] The artificial intelligence module is used to determine the optimal growth environment for the crop at the target location based on the crop environment data and crop growth data, using artificial intelligence algorithms, and then generate control commands. The artificial intelligence module runs the artificial intelligence algorithm, inputs the crop environment data and crop growth data measured by the sensing device, outputs an environmental control strategy, and controls the environmental control device to regulate the crop growth environment.

[0038] The artificial intelligence algorithm takes environmental data vectors, RGB images, and other data as input. The AI ​​model determines the growth stage, and based on this stage, it queries a basic mapping table to obtain the target environmental range and determine the initial setpoint. It then performs contextual fine-tuning based on on-site context rules. Finally, a lightweight learning-based correction module performs minor adjustments within safe boundaries, outputting the optimal environmental parameter setpoint for this location at the current growth stage. This setpoint serves as a reference value for the control layer and is decoded into specific control commands for designated execution devices, achieving closed-loop control of the crop growth environment.

[0039] The growth assessment stage uses a lightweight visual backbone network to extract representations from RGB images, inputs them into a small classifier, outputs the probability distribution of each growth stage, and provides the most probable stage as the assessment result. The system sets a confidence threshold; when the confidence level of a stage assessment falls below the threshold, a lookup table and rule fine-tuning approach are used to ensure safe decision-making under uncertainty.

[0040] The basic mapping table, developed by agronomic experts based on historical high-yield or high-quality batches, provides reasonable ranges for environmental targets at each growth stage. This information is used to construct a basic mapping table for decision support. The algorithm queries the range for that stage based on the growth stage determination, and selects the center of the range or a value biased towards one side as the initial setpoint, considering energy consumption and quality preferences. The bias direction is determined by the strategy: during peak electricity price periods, it favors energy conservation; during periods of increased disease risk, it favors safety. Scenario rules are overlaid for fine-tuning, ensuring the setpoint closely reflects the current state.

[0041] The on-site context rules include: automatically reducing light intensity and lowering the temperature by one to two degrees Celsius at night; appropriately tightening the upper limits of carbon dioxide and light intensity during periods of high electricity prices or peak power load to reduce energy consumption; and allowing light targets to yield in stages during extreme weather or when ventilation is limited to ensure that temperature and humidity safety are prioritized.

[0042] A lightweight learning-based correction module filters historical data for data that requires less time to reach the target interval, has smaller deviations after stabilization, and consumes less energy to reach the target. It extracts the offset of the final stable value relative to the center value of the target database and uses this offset as a supervision label. The setpoint, modified by fusing features, current environmental values, and scenario rules, serves as the metadata for each training sample. A small, two-layer fully connected network is used, taking sample metadata and its corresponding supervision label as input and outputting a small correction value for environmental parameters. An amplitude limit is set at the network's end to ensure the correction amount remains within a preset range. During training, a loss function insensitive to outliers is used to keep the model smooth near boundaries. The control layer calculates the deviation between the corrected setpoint and the current environment and controls the specified execution device based on the deviation value.

[0043] Examples of environmental control strategies: The environmental parameters for the current crop growth stage, such as carbon dioxide, temperature, humidity, and light intensity, are 2000, 21, 40, and 12000, respectively. The currently measured values ​​are 1000, 30, 60, and 10000. At this point, the carbon dioxide control equipment needs to increase the target concentration to 2000, the temperature control equipment needs to decrease the target temperature to 21, the humidity control equipment needs to decrease the target humidity to 40, and the supplemental lighting equipment needs to increase the target light intensity to 12000.

[0044] Environmental control strategy determination process: For example, if the current crop is cucumber, the equipment can collect environmental and crop growth data for a season of cucumbers. Through manual labeling, the optimal growth environment parameters for different crop growth stages are determined. Artificial intelligence algorithms are then used to link the crop growth data and environmental data, forming an AI algorithm for intelligent environmental control of cucumbers. When the next season of cucumbers is planted, the equipment automatically identifies the current growth stage of the cucumbers based on the collected data, and then uses the AI ​​algorithm combined with the current environmental data to output an environmental control strategy.

[0045] The second ranging module is used to measure the distance between the edge computing device and the sensing device, and to determine whether the sensing device is at the starting point.

[0046] The horizontal movement module is used to drive the edge computing device to move the sensing device horizontally on the track.

[0047] The vertical movement module is used to move the sensing device up and down.

[0048] The second wireless communication module is used to send charging request commands and power-off request commands to the first wireless communication module, to the sensing device to send crop environment data and crop growth data acquisition commands, and to the environmental control device to send the control commands. The second wireless communication module is responsible for communicating with the wireless charging device to send charging requests (charging request commands) and power-off requests (power-off request commands), communicating with the sensing device to acquire crop environment data and crop growth data, and communicating with the environmental control device to send specific environmental control commands.

[0049] The second transmitting coil module is used to charge the sensing device.

[0050] The second control module is used to schedule the first receiving coil, the second power module, the artificial intelligence module, the second ranging module, the horizontal movement module, the vertical movement module, the second wireless communication module, and the second transmitting coil module in real time to complete the various functions of the edge computing device.

[0051] The sensing device is used to collect crop environmental data and crop growth data at the target location within the facility agriculture building; the crop environmental data includes temperature, humidity, carbon dioxide concentration, and light intensity.

[0052] As an alternative implementation method, such as Figure 4 As shown, the sensing module includes: a second receiving coil, a third power supply module, a third control module, an environmental sensing module, a growth sensing module, and a third wireless communication module.

[0053] The second receiving coil is used to receive the magnetic signal emitted by the second transmitting coil module and convert it into electrical energy to charge the third power module.

[0054] The third power supply module is used to supply power to the third control module, the environmental sensing module, the growth sensing module and the third wireless communication module.

[0055] The environmental sensing module is used to acquire crop environmental data at the target location within the facility agriculture building. The environmental sensing module is responsible for acquiring environmental data such as air temperature, humidity, carbon dioxide levels, and light intensity.

[0056] The crop growth monitoring module is used to acquire crop growth data at target locations within the agricultural facility. The module, which acquires crop growth status data, primarily utilizes image sensors and hyperspectral sensors.

[0057] The third wireless communication module is used to upload the crop environment data and the crop growth data to the edge computing device.

[0058] The third control module is used to schedule the second receiving coil, the third power supply module, the environmental sensing module, the growth sensing module, and the third wireless communication module in real time to complete the various functions of the sensing device.

[0059] The environmental control device is used to regulate the environmental data of the target location within the facility agriculture building according to the control command, so that the environmental data of the target location reaches the optimal growth environment for the crop at its growth stage.

[0060] As an alternative implementation method, such as Figure 5 As shown, the environmental control device includes: a fourth power supply module, a fourth control module, an execution module, and a fourth wireless communication module. Multiple environmental control devices can be deployed as needed.

[0061] The fourth power supply module is used to supply power to the fourth control module, the execution module and the fourth wireless communication module.

[0062] The execution module is used to regulate the environmental data at the target location within the agricultural facility building according to the control commands, so that the environmental data at the target location reaches the optimal growth environment for the crop at its current growth stage. The execution module includes a humidifier, air conditioner, carbon dioxide supplementation equipment, and a fan. The execution module is responsible for regulating the crop growth environment and typically includes environmental control equipment such as humidifiers, air conditioners, carbon dioxide supplementation equipment, and fans.

[0063] The fourth wireless communication module is used to receive control commands from the edge computing device.

[0064] The operation process of the intelligent environmental control system for facility agriculture is as follows: First, the track is laid according to the environmental control requirements, and environmental control devices are placed at corresponding locations according to the environmental control range. Then, a wireless charging device is installed at the starting point of the track, and an edge computing device is installed on the track. A sensing device is connected to the vertical movement module of the edge computing device via a rope and is located below the edge computing device. The target location is pre-set and downloaded to the edge computing device, and the subsequent system automatically cycles according to the target location parameters. After the edge computing device reaches the first target location driven by the horizontal movement module, it stops moving. Then, the vertical movement module moves the sensing device down to the target height position via a rope. The edge computing device then sends a data acquisition command to the sensing device through the wireless communication module 2. After receiving the command through the wireless communication module 3, the sensing device begins to acquire crop environmental data and growth data, and transmits the data back to the edge computing device through the wireless communication module 3. After receiving the data, the edge computing device inputs the data into the artificial intelligence module. The artificial intelligence module analyzes the data, determines the optimal environment required for the crop's growth stage at the current target location, generates a control command in real time, and sends it to the nearest environmental control device at the current target location to adjust the environment in real time to achieve the target. Then, the data acquisition and environmental control at the next target location are repeated. After one round, the edge computing device automatically returns to the starting point and sends a charging command to the wireless charging device via the wireless communication module 2. At this time, after receiving the charging command via the wireless communication module 1, the wireless charging device activates the ranging module to measure whether the edge computing device has reached the starting point. If it has, it can charge the edge computing device via the transmitting coil module 1. Simultaneously, the edge computing device measures whether the sensing device is below the starting point via the ranging module 2. If it is, it can charge the sensing device via the transmitting coil module 2. The above actions are repeated at regular intervals to achieve 24-hour unmanned intelligent control of the agricultural crop growth environment to reach the optimal state.

[0065] The intelligent environmental control system for facility agriculture provided in this application has the following technical effects: The use of a track-based mobile measurement method to acquire environmental and crop growth data has advantages such as a large measurement range, low measurement cost, long sensor life unaffected by ground humidity, and easy maintenance.

[0066] By incorporating a growth sensing module into the sensing device, the artificial intelligence module in the edge computing device can analyze the optimal growth environment required for the crop's current growth stage and dynamically adjust the environmental control strategy.

[0067] By incorporating a wireless charging device, the system can operate unattended and intelligently 24 hours a day, ensuring safe power consumption. The system uses a ranging module to measure whether the edge computing device and sensing device have reached the starting position, and charging only begins after confirmation, reducing the energy consumption of constantly activating the wireless transmission module.

[0068] By incorporating edge computing devices, sensor data can be acquired, processed, analyzed, and output in real time, eliminating the need to upload data to the cloud for analysis, thus reducing system operating costs and saving communication resources.

[0069] By employing a track-based mobile measurement method and deploying multiple environmental control devices, it is possible to achieve precise control of the crop growth microenvironment over a smaller area, thereby enabling efficient energy utilization and further reducing production costs.

[0070] 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.

[0071] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An intelligent environmental control system for facility agriculture, characterized in that, include: Tracks, edge computing devices, sensing devices, and environmental control devices; The track uses I-beam steel rails and is suspended from the top of the facility agriculture building; The edge computing device and the sensing device are connected by ropes, with the edge computing device suspended below the track to drive the sensing device; the environmental control device is placed at various locations within the facility agriculture building. The sensing device is used to collect crop environmental data and crop growth data at the target location within the facility agriculture building; the crop environmental data includes temperature, humidity, carbon dioxide concentration, and light intensity; The edge computing device is used to determine the optimal growth environment for the crop at the target location during its growth stage based on the crop environment data and the crop growth data, using artificial intelligence algorithms, and to generate control commands. The environmental control device is used to regulate the environmental data of the target location within the facility agriculture building according to the control command, so that the environmental data of the target location reaches the optimal growth environment for the crop at its growth stage.

2. The intelligent environmental control system for facility agriculture according to claim 1, characterized in that, Also includes: A wireless charging device; the wireless charging device is placed at the starting position of the track; The wireless charging device is used to charge the edge computing device.

3. The intelligent environmental control system for facility agriculture according to claim 2, characterized in that, The wireless charging device includes: a first power module, a first control module, a first ranging module, a first wireless communication module, and a first transmitting coil module; The first power module is used to provide power to the first control module, the first ranging module, the first wireless communication module and the first transmitting coil module; The first wireless communication module is used to receive the edge computing device's request to charge command and request to power off after it is fully charged; The first ranging module is used to measure the distance between the wireless charging device and the edge computing device after the first wireless communication module receives the charging request command, and to determine whether the edge computing device is at the starting point. The first control module is used to control the first transmitting coil module to charge or stop charging the edge computing device.

4. The intelligent environmental control system for facility agriculture according to claim 3, characterized in that, The edge computing device includes: a first receiving coil, a second power module, an artificial intelligence module, a second ranging module, a second control module, a horizontal movement module, a vertical movement module, a second wireless communication module, and a second transmitting coil module; The first receiving coil is used to receive the magnetic signal emitted by the first transmitting coil module and convert it into electrical energy to charge the second power module; The second power module is used to supply power to the artificial intelligence module, the second ranging module, the second control module, the horizontal movement module, the vertical movement module, the second wireless communication module, and the second transmitting coil module; The artificial intelligence module is used to determine the optimal growth environment for the crop at the target location during its growth stage based on the crop environment data and the crop growth data, and to generate control commands. The second ranging module is used to measure the distance between the edge computing device and the sensing device, and to determine whether the sensing device is at the starting point; The horizontal movement module is used to drive the edge computing device to move the sensing device horizontally on the track; The vertical movement module is used to move the sensing device up and down. The second wireless communication module is used to send a request to charge command, a request to power off command, a command to acquire crop environment data and crop growth data to the sensing device, and the control command to the environmental control device; The second transmitting coil module is used to charge the sensing device; The second control module is used to schedule the first receiving coil, the second power supply module, the artificial intelligence module, the second ranging module, the horizontal movement module, the vertical movement module, the second wireless communication module, and the second transmitting coil module in real time.

5. The intelligent environmental control system for facility agriculture according to claim 4, characterized in that, The sensing module includes: a second receiving coil, a third power supply module, a third control module, an environmental sensing module, a growth sensing module, and a third wireless communication module; The second receiving coil is used to receive the magnetic signal emitted by the second transmitting coil module and convert it into electrical energy to charge the third power supply module; The third power supply module is used to supply power to the third control module, the environmental sensing module, the growth sensing module and the third wireless communication module; The environmental sensing module is used to acquire crop environmental data at the target location within the facility agriculture building; The growth monitoring module is used to acquire crop growth data at the target location within the facility agriculture building; The third wireless communication module is used to upload the crop environment data and the crop growth data to the edge computing device; The third control module is used to schedule the second receiving coil, the third power supply module, the environmental sensing module, the growth sensing module, and the third wireless communication module in real time.

6. The intelligent environmental control system for facility agriculture according to claim 5, characterized in that, The growth monitoring module includes an image sensor and a hyperspectral sensor.

7. The intelligent environmental control system for facility agriculture according to claim 5, characterized in that, The environmental control device includes: a fourth power module, a fourth control module, an execution module, and a fourth wireless communication module; The fourth power supply module is used to supply power to the fourth control module, the execution module and the fourth wireless communication module; The execution module is used to adjust the environmental data of the target location within the facility agriculture building according to the control command, so that the environmental data of the target location reaches the optimal growth environment for the crop at its growth stage. The fourth wireless communication module is used to receive control commands from the edge computing device.

8. The intelligent environmental control system for facility agriculture according to claim 7, characterized in that, The execution module includes a humidifier, an air conditioner, a carbon dioxide replenishment device, and a fan.

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