Low-heating light source control method and system suitable for plant growth

Abstract

A low-heating light source control method and system suitable for plant growth relates to the field of light control, and the method comprises the following steps: collecting current environment data in a target environment, plant type data and thermal distribution data of a target plant, and analyzing the growth demand of the plant through a plant growth cycle model to obtain a plant growth cycle model; heat demands and illumination demands of the target plant in different growth stages are obtained, demand data and environmental thermal distribution are considered, an optimal position distribution scheme of a heating light source is determined by adopting a simulation calculation method, and distance data between the heating light source and the target plant are obtained; the position relation between the light sources and the plants is determined in a three-dimensional space coordinate system, the optimal irradiation angle of each light source can be calculated according to the relative positions of the light sources and the plants, finally, accurate angle control is conducted on the heating light sources, the preset optimal irradiation angle is achieved, appropriate illumination and heat are provided for the plants, and therefore the plant quality is improved. Therefore, the plant growth effect is prevented from being influenced.

Description

Technical Field

[0001] The present application relates to the field of lighting control, and in particular to a method and system for controlling a low-heat light source suitable for plant growth. Background Art

[0002] With the growth of global population and the acceleration of urbanization, agricultural production is facing greater and greater challenges. In order to improve the yield and quality of crops, modern agricultural technology continues to develop, especially in the field of plant growth lighting. The use of artificial light sources has become increasingly important. The rational use of artificial light sources can not only extend the illumination time of plants and promote plant photosynthesis, but also regulate the growth cycle of plants to a certain extent and improve the yield of crops.

[0003] In the relevant technology, the plant growth light sources widely used in the market mainly include high pressure sodium lamps, fluorescent lamps, LED lamps, etc. These light sources meet the needs of plant growth by providing appropriate light intensity and spectral distribution. Traditional plant growth light sources usually use fixed light source positions and irradiation angles, and control the coverage and uniformity of light by manually adjusting the height and irradiation direction of the light source to ensure that the plants can receive light evenly.

[0004] However, the high heat generated by traditional light sources not only increases energy consumption, but may also cause heat stress to plants, affecting their normal growth. Summary of the invention

[0005] The present application provides a low-heat light source control method and system suitable for plant growth, which are used to avoid affecting the growth effect of plants.

[0006] In the first aspect, the present application provides a low-heat light source control method suitable for plant growth, which is applied to a low-heat light source control system, and the method includes: collecting current environmental data in a target environment, plant type data of a target plant, and thermal distribution data in the target environment, wherein the target environment includes a plurality of target plants; inputting the plant type data into a plant growth cycle model to obtain the heat demand and light demand of the target plant in each preset growth stage; calculating and generating a heat light source position distribution based on the heat demand, the light demand, and the thermal distribution data; obtaining distance data from the heat light source to the target plant; determining a preset irradiation angle of the heat light source based on the heat light source position distribution and the distance data; and controlling the heat light source based on the irradiation angle.

[0007] By adopting the above technical scheme, the current environmental data in the target environment, the plant type data of the target plant and the thermal distribution data are collected, and the growth needs of the plants are analyzed through the plant growth cycle model to obtain the heat and light needs of the target plants at different growth stages. On the basis of clarifying the plant needs, the simulation calculation method is used to determine the optimal position distribution scheme of the heating light source, obtain the distance data between the heating light source and the target plant, and determine the position relationship between the light source and the plant in the three-dimensional space coordinate system. According to the relative position of the light source and the plant, the optimal irradiation angle of each light source can be calculated. Finally, by accurately controlling the angle of the heating light source, the preset optimal irradiation angle is achieved to provide the plants with appropriate light and heat, thereby avoiding affecting the growth effect of the plants.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the step of calculating and generating the distribution of the positions of the heating light sources based on the heat demand, the lighting demand and the thermal distribution data specifically includes: calculating the actual heat data of each of the environmental grid units based on the thermal distribution data; dividing the target environment into multiple environmental grid units, and calculating the heat regulation demand of each of the environmental grid units based on the heat demand and the actual heat data; calculating the comprehensive demand of each of the environmental grid units based on the heat regulation demand and the lighting demand; simulating candidate positions of heating light sources in the target environment, and obtaining the simulated heat and simulated light intensity of each of the environmental grid units; calculating the average satisfaction of all the environmental grid units based on the simulated heat, the simulated lighting and the comprehensive demand; repeating the step of simulating candidate positions of heating light sources in the target environment so that the average satisfaction is greater than a preset satisfaction threshold, and using the obtained simulated heating light source candidate positions greater than the preset satisfaction threshold as the heating light source position distribution.

[0009] By adopting the above technical solution, the current actual heat level of each environmental grid unit is calculated based on the thermal distribution data, and the heat regulation amount that needs to be increased or decreased for each grid is determined according to the heat demand of the plant to meet the demand. After clarifying the demand adjustment situation of each area, the heat demand and light demand are considered to determine the comprehensive environmental regulation demand of each grid unit. Then, through multiple simulations and calculations of candidate locations of heating light sources, the light and heat effect of each location is predicted, and through iterative optimization, a heating light source location distribution scheme with a high average satisfaction is obtained, which can determine the optimal light source layout scheme that can evenly improve the environment and meet the needs of crop growth.

[0010] In combination with some embodiments of the first aspect, in some embodiments, the step of determining the preset illumination angle of the heating light source based on the position distribution of the heating light source and the distance data specifically includes: establishing a three-dimensional coordinate system based on the target environment, and mapping each of the heating light sources and the target plant corresponding to the position distribution of the heating light source to the three-dimensional coordinate system; calculating the position vector of each target plant within the illumination range of the heating light source; calculating the initial illumination angle of each heating light source based on the position distribution of each target plant within the illumination range; and correcting the initial illumination angle based on the growth height of the target plant to obtain the preset illumination angle.

[0011] By adopting the above technical solution, a three-dimensional coordinate system is established, the spatial coordinate information of each light source and plant is determined, and the direction vector of the light source pointing to the plant is calculated. Based on the direction vector, the initial pitch angle and azimuth angle of the light source can be calculated respectively to indicate its initial irradiation direction. Then, in order to irradiate the entire plant, the initial angle of the light source is adjusted according to the growth conditions of the plant to point to the optimal direction of the plant. The calculated and optimized irradiation angle parameters of each light source can be obtained. By determining the precise irradiation angle, the light and heat emitted by the light source can better cover every part of the plant and meet the growth needs of the crop.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the step of calculating the initial irradiation angle of each of the heating light sources based on the position distribution of each target plant within the irradiation range specifically includes: calculating the geometric center point of each of the target plants within the irradiation range of the heating light source; calculating the vector from the heating light source to the geometric center point to obtain a unit vector; calculating the initial pitch angle and initial azimuth angle of the heating light source based on the unit vector, and using the initial pitch angle and the initial azimuth angle as the initial irradiation angle.

[0013] By adopting the above technical solution, first, the geometric center point of the target plant within the illumination range of each heating light source is calculated, the spatial position of the plant is accurately located, the vector pointing from the light source to the center point of the plant is calculated, the directional relationship between the two is abstractly represented, the vector is converted into a standardized unit vector, the position information is removed, and only the directional characteristics are retained. The initial pitch angle and azimuth angle of the light source are calculated based on the unit vector to represent its initial unoptimized illumination angle. Through vector calculation and coordinate transformation, the initial illumination angle representing the light source pointing to the plant can be obtained.

[0014] In combination with some embodiments of the first aspect, in some embodiments, after the step of controlling the heat-generating light source according to the illumination angle, the method further includes: monitoring the temperature change and light intensity change of the environmental grid unit; calculating the actual heat supply within the environmental grid unit according to the temperature change, and calculating the actual light supply within the environmental grid unit according to the light intensity change; comparing the actual heat supply with the heat demand to obtain a heat deviation value, and comparing the actual light supply with the light demand to obtain a light deviation value; when the heat deviation value or the light deviation value exceeds a preset threshold, adjusting the power of the heat-generating light source to a preset power.

[0015] By adopting the above technical solution, the angle of the heating light source is precisely controlled according to the preset optimal irradiation angle, the temperature and light changes in the environmental grid unit are monitored in real time, the effect of the light source adjustment is evaluated, the actual light and heat supply in each grid unit is calculated, and compared with the plant requirements to determine whether there is a deviation. If the deviation of light or temperature exceeds the threshold, the light source power is adjusted accordingly to make the environmental parameters close to the plant requirements. Closed-loop control of the light source irradiation angle and output power can be achieved, so that the plant growth environment parameters are continuously maintained in the optimal state.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the steps of comparing the actual heat supply with the heat demand to obtain a heat deviation value, and comparing the actual light supply with the light demand to obtain a light deviation value, the method further includes: when the heat deviation value or the light deviation value exceeds a maximum threshold, sending a prompt message to the target client.

[0017] By adopting the above technical solution, when it is determined that there is a deviation exceeding the threshold between the ambient light and heat supply and the plant demand, a prompt message is actively sent to the user terminal. When there is an abnormality in the light or temperature control, which may have a negative impact on the growth of plants, the user can be notified in time to pay attention to the problem. After receiving the prompt, the user can check the light source equipment for failure, or adjust the control strategy parameters to adjust the environmental parameters back to the normal range. Through active prompt information feedback, users can better monitor the operating status of the light source, ensure that the plant growth environment is in the best conditions, and avoid insufficient or excessive supply.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of sending a prompt message to the target client when the heat deviation value or the light deviation value exceeds the maximum threshold, the method also includes: comparing the current image of the target plant with the historical image of the target plant to obtain the change rate of the target plant; and sending the change rate to the target client.

[0019] By adopting the above technical solution, after sending the user a prompt message of abnormal environmental control, the system further obtains images of the target plant at different periods. The two images are compared using image processing technology to calculate the growth change of the plant and obtain a quantitative change rate indicator. The change rate result is sent to the user to more intuitively reflect the growth status of the plant. When there is a problem with environmental control, the user can not only receive a prompt message, but also see the quantitative analysis results of the plant growth rate, which can help the user evaluate the impact of the problem on the crop.

[0020] In the second aspect, an embodiment of the present application provides a low-heat light source control system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the low-heat light source control system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions. When the above-mentioned computer program product runs on a low-heat light source control system, the above-mentioned low-heat light source control system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions. When the instructions are executed on a low-heat light source control system, the low-heat light source control system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0023] It can be understood that the low-heat light source control system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. This application collects current environmental data in the target environment, plant type data of the target plants, and thermal distribution data, analyzes the growth needs of the plants through the plant growth cycle model, and obtains the heat and light needs of the target plants at different growth stages. On the basis of clarifying the plant needs, a simulation calculation method is used to determine the optimal position distribution plan of the heating light source, obtain the distance data between the heating light source and the target plant, and determine the position relationship between the light source and the plant in a three-dimensional space coordinate system. According to the relative position of the light source and the plant, the optimal irradiation angle of each light source can be calculated. Finally, by precisely controlling the angle of the heating light source, the preset optimal irradiation angle is achieved to provide the plants with appropriate light and heat, thereby avoiding affecting the growth effect of the plants.

[0025] 2. This application calculates the current actual heat level of each environmental grid unit based on the thermal distribution data, and determines the amount of heat regulation that needs to be increased or decreased for each grid according to the heat demand of the plant to meet the demand. After clarifying the demand adjustment situation of each area, the heat demand and light demand are considered to determine the comprehensive environmental regulation demand of each grid unit. Then, through multiple simulations and calculations of candidate locations of heating light sources, the light and heat effect of each location is predicted, and through iterative optimization, a heating light source location distribution plan with a high average satisfaction is obtained, which can determine the optimal light source layout plan that can evenly improve the environment and meet the needs of crop growth.

[0026] 3. The present application establishes a three-dimensional coordinate system, determines the spatial coordinate information of each light source and plant, and calculates the direction vector of the light source pointing to the plant. Based on the direction vector, the initial pitch angle and azimuth of the light source can be calculated respectively to indicate its initial irradiation direction, and then to irradiate the entire plant, the initial angle of the light source is adjusted according to the growth conditions of the plant to point to the optimal direction of the plant. The calculated and optimized irradiation angle parameters of each light source can be obtained. By determining the precise irradiation angle, the light and heat emitted by the light source can better cover every part of the plant and meet the growth needs of the crop. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of a low-heat light source control method suitable for plant growth in an embodiment of the present application; Figure 2 is another flow chart of a method for controlling a low-heat-generating light source suitable for plant growth in an embodiment of the present application; Figure 3 It is a schematic diagram of the structure of a physical device of a low-heat light source control system in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0030] For ease of understanding, the following is a description of the process of the method provided by this implementation. Figure 1 , which is a flow chart of a method for controlling a low-heat light source suitable for plant growth in an embodiment of the present application.

[0031] S101, collecting current environmental data in a target environment, plant type data of a target plant, and thermal distribution data in the target environment, wherein the target environment includes a plurality of the target plants.

[0032] Among them, the target environment refers to a specific area that requires low-heat light source control, such as a closed or semi-enclosed planting space such as a greenhouse or plant factory. Current environment data refers to parameters such as real-time temperature, humidity, and carbon dioxide concentration in the target environment. Plant type data is used to indicate information such as the type and variety of the target plant. Thermal distribution data refers to the temperature distribution at each location in the target environment. Target plants refer to individual plants that require light and temperature control.

[0033] Specifically, before starting the low-heat light source control, the system first needs to obtain the basic information of the target environment and plant information. The system collects environmental parameters such as temperature and humidity in the target environment through various sensors, and obtains information on the plant species. In addition, the system also needs to collect thermal distribution data in the target environment through thermal imaging equipment or multi-point temperature sensors to understand the temperature distribution in the environment.

[0034] In some embodiments, data collection can be achieved in a variety of ways: Optionally, the system can collect data through the following steps: arrange a temperature and humidity sensor network in the target environment and regularly collect environmental parameters; identify the type and growth status of the target plant through an image recognition system; use an infrared thermal imaging camera to scan the target environment and generate a thermal distribution map. Optionally, the system can also: collect environmental data in real time through an Internet of Things device; enter plant species information by manual input; use a distributed temperature sensor array to collect thermal distribution data. It is understandable that other methods can also be used to achieve data collection, such as using drones to scan the environment, etc., which are not limited here.

[0035] S102: Input the plant type data into a plant growth cycle model to obtain the heat demand and light demand of the target plant at each preset growth stage.

[0036] Among them, the plant growth cycle model refers to a mathematical model that describes the environmental conditions required by different plants at different stages of their growth. The preset growth stage represents the key period in the plant growth process, such as the germination period, seedling period, flowering period, etc. The heat requirement refers to the temperature range required by the plant at a specific growth stage. The light requirement refers to the light intensity and duration required by the plant at a specific growth stage.

[0037] Specifically, the system inputs the collected plant type data into a pre-established plant growth cycle model. The model is built based on a large amount of historical data and plant physiological knowledge, and can predict the environmental conditions required by the plant species and growth stage.

[0038] In some embodiments, the application of the plant growth cycle model can be implemented in a variety of ways: Optionally, the system can take the following steps: retrieve the growth cycle model corresponding to the input plant type from the database; input the current plant growth stage information into the model; run the model algorithm to calculate the heat and light demand values ​​for each preset growth stage. Optionally, the system can also: use a machine learning algorithm to automatically select the most suitable model based on the input plant type; dynamically adjust the model parameters in combination with real-time environmental data; output a detailed demand curve, including specific demand values ​​for different time periods. It is understandable that other methods can also be used to implement model application.

[0039] Specifically, the plant growth cycle model is constructed as follows: first, by obtaining the historical growth data, experimental data and farm data of all plants in the target environment, the historical growth data records the growth of different types of plants under various environmental conditions, such as temperature, humidity, light intensity, etc. The experimental data is the data that records the response of plants at different growth stages by controlling the environmental conditions in the laboratory. The farm data is the plant growth records from the actual farm, including environmental conditions and yield data; the input data of the plant growth cycle model mainly include: environmental data, the temperature, humidity, light intensity, etc. of the current environment; plant type data, information such as the type and variety of the plant; growth stage data, the current growth stage of the plant, such as the germination stage, seedling stage, flowering stage, etc.; the output data of the model mainly include heat demand, the temperature range required for plants at a specific growth stage, and light demand, the light intensity and duration required for plants at a specific growth stage.

[0040] Collect plant growth-related data from different data sources, clean and normalize the collected data to ensure data quality, annotate the data according to the growth stage of the plant, generate training samples, and then select the random forest model to build the plant growth cycle model. The preprocessed data set is divided into training set, validation set and test set. The training set is used to train the model, the validation set is used to adjust parameters and select the best model, and the test set is used to evaluate the final performance of the model. The input features are selected to ensure that the model uses the most meaningful features for training. Common methods include calculating the importance of features and using cross-validation for feature screening. The training set is used to train the random forest model. During the training process, the model performance is optimized by adjusting the parameters of the random forest (such as the number of trees, maximum depth, etc.). The trained model is evaluated using the validation set, and the model parameters are adjusted according to the validation results to improve the generalization ability of the model. The final model is evaluated using an independent test set to ensure that the model can maintain good performance on unseen data. After training, the model can output the heat and light requirements of the plant at a specific growth stage based on the input environmental data, plant type data and growth stage data.

[0041] S103, calculating and generating the heat source position distribution according to the heat demand, the lighting demand and the thermal distribution data.

[0042] Among them, heat demand indicates the temperature range required by the target plant at a specific growth stage. Light demand refers to the light intensity and duration required by the target plant at a specific growth stage. Thermal distribution data is used to indicate the temperature distribution at various locations in the target environment. The location distribution of heating light sources refers to the reasonable arrangement of the spatial layout of heating light sources in the target environment. For example, in a greenhouse, the heat demand is 20-25℃, and the light demand is 1000μmol / m² / s light intensity for 12 hours a day. The thermal distribution data shows that the temperature in some corners of the greenhouse is lower, so the location distribution of heating light sources needs to increase the light source density in these areas.

[0043] Specifically, the system will comprehensively consider the needs of the plants and the current environmental conditions, calculate the impact of each possible light source position on the environment, and ultimately come up with a light source layout plan that can both meet the needs of the plants and evenly distribute heat. During the calculation process, the system will consider factors such as the heat generation characteristics of the light source, the range of illumination, and the heat propagation pattern, and optimize it in combination with the growth stage and specific needs of the plants.

[0044] In some embodiments, the calculation of the position distribution of the heat source can be implemented in a variety of ways: Optionally, the system can use a combination of grid division and optimization algorithm. First, the target environment is divided into multiple uniform three-dimensional grid units, each unit represents a possible light source position. Then the current heat and light levels of each grid unit are calculated, compared with the target plant requirements, and the gap value is obtained. Then, an optimization method such as a genetic algorithm or a simulated annealing algorithm is used to iteratively calculate the best combination of light source positions with the goal of minimizing the overall gap. In each iteration, the algorithm adjusts the position and number of light sources according to the performance of the current solution, and recalculates the environmental parameters until the optimal solution that meets the conditions is found. Optionally, the system can also use a combination of three-dimensional thermal model and illumination simulation. First, a detailed three-dimensional model of the target environment is established, including information such as spatial structure and material properties. Then, computational fluid dynamics (CFD) technology is used to simulate the impact of different light source layouts on the ambient temperature distribution. At the same time, a ray tracing algorithm is used to simulate the lighting effect of the light source on the environment. By repeatedly adjusting the light source position and parameters, the system can find a light source layout solution that can best meet the needs of the plants.

[0045] S104: Acquire distance data from the heating light source to the target plant.

[0046] Among them, the heat-generating light source refers to a light source device that can provide both light and heat, such as an LED growth lamp. The target plant refers to the individual plant that needs light and temperature control. The distance data is used to indicate the spatial distance between the heat-generating light source and the target plant. For example, in a plant factory, the heat-generating light source may be an LED lamp hanging from the ceiling, and the target plant is a vegetable planted on the ground, and the distance data may be 1.5 meters.

[0047] Specifically, after determining the location distribution of the heat-generating light sources, the system needs to accurately calculate the distance from each light source to the surrounding target plants. The purpose of this step is to provide a basis for subsequent adjustment of the illumination angle and intensity of the light source. In actual operation, the system will consider factors such as the installation height of the light source, the growth height of the plant, and the spacing between plants. For large-scale planting facilities, multiple ranging points may be required to ensure the accuracy of the measurement.

[0048] In some embodiments, the distance from the heating light source to the target plant can be obtained in a variety of ways: Optionally, the system can use laser ranging technology combined with an automated control system. First, multiple high-precision laser rangefinders are installed in the planting area, and the rangefinders can rotate 360 ​​degrees and accurately position. Then, the system controls the rangefinder to automatically scan the entire planting area, identify and record the three-dimensional coordinates of each heating light source and target plant. Then, the system uses these coordinate data to calculate the straight-line distance from each light source to all plants within its irradiation range through spatial geometry.

[0049] Optionally, the system can also use computer vision technology combined with deep learning algorithms. First, multiple high-definition cameras are installed in the planting area, which can capture stereo images of the target environment. Then, deep learning algorithms, such as convolutional neural networks (CNN) and target detection algorithms (such as YOLO or Faster R-CNN), are used to process the captured images to automatically identify and locate each heating light source and target plant. Next, the system uses stereo vision algorithms, such as structured light or binocular stereo vision, to calculate the depth information of each object in the scene, thereby constructing a three-dimensional point cloud model of the entire planting environment. Finally, based on this precise three-dimensional model, the system calculates the precise distance from each light source to the surrounding plants. This method can not only obtain distance data, but also monitor the growth status of plants in real time. It is understandable that other methods can also be used to obtain distance data, such as using an ultrasonic array ranging system, or combining radio frequency identification (RFID) technology for individual plant identification and positioning, etc., which are not limited here.

[0050] S105: Determine a preset irradiation angle of the heating light source according to the position distribution of the heating light source and the distance data.

[0051] Among them, the location distribution of the heating light sources represents the spatial layout arrangement of the heating light sources in the target environment. The distance data refers to the spatial distance information from the heating light source to the target plant. The preset irradiation angle is used to indicate the optimal angle at which the heating light source irradiates the target plant. A heating light source refers to a light source device that can provide both light and heat, such as an LED grow light or an infrared heating lamp. For example, in a smart greenhouse, the location distribution of the heating light sources may show that the LED grow lights are evenly distributed on the ceiling, and the distance data shows that the vertical distance from the lamp to the top of the plant is 1 meter, then the preset irradiation angle may be determined to be 45 degrees to ensure that the light evenly covers the surface of the plant.

[0052] Specifically, after obtaining the position distribution and distance data of the heating light source, the system needs to calculate the optimal irradiation angle for each heating light source. The purpose of this step is to ensure that each target plant can receive appropriate light intensity and heat. The system will comprehensively consider the luminous characteristics of the light source, the heat distribution pattern, the morphological characteristics of the plant, and the surrounding environmental factors to determine the optimal irradiation angle. During the calculation process, the light distribution and heat transfer effects at different angles are simulated and optimized in combination with the growth needs of the plant.

[0053] In some embodiments, the determination of the preset irradiation angle of the heat source can be achieved in a variety of ways: Optionally, the system can use a ray tracing algorithm combined with a heat transfer model. First, the system builds a three-dimensional model of the target environment based on the position distribution and distance data of the heat source. Then, the ray tracing algorithm is used to simulate the propagation path and intensity distribution of light in the environment at different angles. At the same time, combined with the heat transfer model, the diffusion of heat in space at different angles is calculated. Then, the system compares the simulation results with the light and heat requirements of the plant to evaluate the effect of each angle. Finally, through iterative optimization, the best combination of irradiation angles that can best meet the needs of the plant is found. Optionally, the system can also use machine learning methods combined with an expert knowledge base. First, a large database containing various plant growth conditions, light source characteristics, and environmental parameters is established. Then, a deep learning algorithm, such as a convolutional neural network (CNN) or a long short-term memory network (LSTM), is used to train a model that can predict the optimal irradiation angle. During the training process, the model learns the complex relationship between factors such as light source position, distance, plant characteristics, and the optimal irradiation angle. Then, the expert knowledge is encoded into a decision tree or fuzzy logic system to correct and optimize the output of the machine learning model. Finally, the system applies the trained model to the actual environment and quickly calculates the optimal illumination angle for each light source based on the real-time light source position and distance data. It is understandable that other methods can also be used to determine the preset illumination angle, such as using genetic algorithms to optimize angle combinations, or combining computational fluid dynamics (CFD) technology to simulate microclimate changes at different angles, etc., which are not limited here.

[0054] S106: Control the heat source according to the irradiation angle.

[0055] The irradiation angle refers to the optimal angle at which the heat-generating light source irradiates the target plant. A heat-generating light source refers to a light source device that can provide both light and heat. Control refers to the adjustment and management of various parameters of the heat-generating light source. For example, in a smart plant factory, the system may adjust the irradiation angle of the LED growth light to 30 degrees and control the pitch mechanism of the lamp accordingly to keep it at this optimal angle.

[0056] Specifically, after determining the preset irradiation angle of each heating light source, the system needs to precisely control the light source to achieve these angles. The purpose of this step is to convert the theoretically calculated optimal angle into actual light source adjustment, thereby creating the best growth environment for plants. The system will first detect the current state of each heating light source, including its current angle, brightness, temperature and other parameters. The system will then calculate the adjustment required from the current state to the target irradiation angle. When making angle adjustments, the system also needs to synchronously adjust other parameters of the light source, such as light intensity and spectral distribution, to ensure that the growth needs of the plants are still met at the new angle.

[0057] In some embodiments, the control of the heat-generating light source can be achieved in a variety of ways: Optionally, the system can use a closed-loop feedback control system. First, a high-precision angle sensor and a temperature sensor are installed on each heat-generating light source to monitor the current angle and operating temperature of the light source in real time. Then, the system inputs the preset irradiation angle into the controller as the target value. The controller compares the difference between the target angle and the current angle and calculates the required adjustment amount. Then, the controller sends a control signal to the motor drive of the light source to drive the light source to rotate to the target angle. During the adjustment process, the system continuously monitors the angle change and temperature change, and fine-tunes the control parameters in real time according to the feedback data to ensure that the target angle is accurately reached and stably maintained. At the same time, the system automatically adjusts the power output of the light source according to the angle change to maintain the constant light intensity received by the plant. Optionally, the system can also use a distributed intelligent control network. First, each heat-generating light source is equipped with a microprocessor control unit, which can independently control the angle, brightness and spectrum of the light source. Then, all control units are connected to a central management system to form an intelligent Internet of Things network. The central system sends preset irradiation angle instructions to each control unit. After receiving the command, each control unit will independently calculate the best path to achieve the target angle based on its own position and surrounding environment parameters.

[0058] The following is a more detailed description of the process of the method provided by this implementation. Figure 2, is another flow chart of a low-heat light source control method suitable for plant growth in an embodiment of the present application.

[0059] S201, collecting current environmental data in a target environment, plant type data of a target plant, and thermal distribution data in the target environment, wherein the target environment includes a plurality of the target plants.

[0060] It can be understood that this step is similar to step S101 and will not be described in detail here.

[0061] S202: Input the plant type data into a plant growth cycle model to obtain the heat demand and light demand of the target plant at each preset growth stage.

[0062] It can be understood that this step is similar to step S102 and will not be described in detail here.

[0063] S203, calculating and generating the heat source position distribution according to the heat demand, the lighting demand and the thermal distribution data.

[0064] It can be understood that this step is similar to step S103 and will not be described in detail here.

[0065] S204: Calculate actual heat data of each environmental grid unit according to the thermal distribution data.

[0066] First, actual heat data refers to the actual temperature value within the environmental grid unit. Environmental grid units refer to the units that divide the target environment into multiple three-dimensional grids for the convenience of calculation and analysis. Thermal distribution data includes the temperature monitoring values ​​of various locations within the target environment.

[0067] Specifically, after obtaining the thermal distribution data in the target environment, this step is to calculate the average temperature or temperature range in each environmental grid unit according to the temperature values ​​of each monitored position as the actual thermal data of the grid unit.

[0068] For example, if there are multiple temperature sensors in the environment, the temperatures monitored are: sensor A 25°C, sensor B 24°C, sensor C 26°C. If these three sensors are located in the same environmental grid unit, the actual thermal data of the grid unit can be set to (25+24+26) / 3=25°C.

[0069] S205: Divide the target environment into a plurality of environmental grid units, and calculate the heat regulation requirement of each of the environmental grid units according to the heat requirement and the actual heat data.

[0070] First, the target environment refers to the entire physical space that needs to be temperature controlled, such as a greenhouse, plant factory, etc. The environmental grid unit is to divide the target environment into multiple small three-dimensional grid units for calculation convenience. The heat demand refers to the temperature conditions required by the plant at each growth stage. The actual heat data is the actual temperature value of each grid unit. The heat regulation demand is the amount of heat that each grid unit needs to increase or decrease to meet the plant's needs.

[0071] Specifically, this step first divides the target environment into multiple three-dimensional grids, and then the system reads the actual heat data of each grid unit, that is, the actual temperature, and calculates the amount of heat that needs to be increased or decreased in the grid unit based on the heat demand of the plant, that is, the heat regulation demand. For example, if the actual temperature of a grid unit is 22°C, but the heat demand of the plant is 25°C, the heat regulation demand of the grid unit is to increase by 3°C. By calculating the heat regulation demand of each grid unit, the areas in the environment that need to increase or decrease heat can be clearly identified.

[0072] S206: Calculate the comprehensive demand of each environmental grid unit according to the heat regulation demand and the lighting demand.

[0073] First, the heat regulation demand refers to the amount of heat that needs to be added or subtracted from each environmental grid cell to meet the growth needs of the plant. The light demand refers to the light conditions that the plant needs at different growth stages. The comprehensive demand refers to the overall environmental demand of each grid cell after considering the heat demand and light demand.

[0074] Specifically, after obtaining the heat regulation requirements of each grid unit and the light requirements of the plants, the system will combine the two and calculate the comprehensive environmental requirements of each grid unit. For example, if the heat requirement of a grid unit is to increase by 5°C and the light requirement is 1000 lumens of light for 12 hours per day, the comprehensive requirement of the grid unit can be expressed as "the temperature needs to increase by 5°C and the light requirement is 1000 lumens of light for 12 hours per day".

[0075] S207, simulating candidate locations of heat-generating light sources in the target environment, and obtaining simulated heat and simulated light intensity of each grid unit of the environment.

[0076] First, the target environment is the entire physical space that needs to be temperature controlled. Simulation is the prediction of a situation through a computer program. Heat source candidate locations are possible locations for light sources. Simulated heat and light intensity are computer-estimated temperature and light conditions.

[0077] Specifically, this step is that the system simulates different candidate locations for placing heat-generating light sources in the target environment, and calculates the impact of each location on the heat and light of the environmental grid unit to obtain simulated heat and light intensity data. The system can perform multiple simulation calculations by establishing a heat conduction model, a light propagation model, etc., to predict the impact of different light source layout schemes on environmental parameters, and provide a basis for the subsequent determination of the optimal light source position.

[0078] For example, it can be simulated that a 100W light source is placed in grid unit A. It is calculated that it will increase the temperature of the grid by 3°C and the light intensity by 500 lumens.

[0079] S208: Calculate the average satisfaction of all the environmental grid cells according to the simulated heat, the simulated light and the comprehensive demand.

[0080] First, simulated heat is the predicted value of the temperature change after placing a light source in each grid cell. Simulated light is the predicted value of the light conditions. Comprehensive demand is the overall demand of the grid cell after considering heat and light demand. Average satisfaction is the degree to which all grid cell demands are met.

[0081] Specifically, in this step, the system comprehensively considers the simulated heat value, simulated light prediction value and comprehensive environmental requirements of each grid unit to calculate the average degree to which the requirements of all grid units are met, that is, the average satisfaction.

[0082] For example, the target environment is divided into 100 grid cells, and each grid cell is simulated to obtain simulated heat and simulated light data. The simulated data of grid cell 1 is: simulated heat increases by 2°C, and simulated light increases by 300 lumens; the comprehensive demand of grid cell 1 is: the temperature needs to increase by 3°C, and 1200 lumens of light is needed for 8 hours a day. Similar calculations are performed for each grid cell to obtain their respective simulated heat, simulated light, and comprehensive demand data. The system then calculates the satisfaction for each grid cell, which can be calculated using the algorithm of satisfying the percentage weight of heat demand A + satisfying the percentage weight of light demand B. Finally, the average satisfaction of the 100 grid cells is taken to obtain the average satisfaction.

[0083] S209, repeatedly executing the step of simulating candidate positions of heating light sources in the target environment so that the average satisfaction is greater than a preset satisfaction threshold, and using the obtained simulated heating light source candidate positions greater than the preset satisfaction threshold as the heating light source position distribution.

[0084] First, the preset satisfaction threshold is the minimum average satisfaction value required by the system. The heat source position distribution is the final placement layout plan of the heat source.

[0085] Specifically, this step is that the system repeatedly simulates placing light sources at different candidate positions and compares the average satisfaction of different solutions until a solution with an average satisfaction higher than a preset threshold is found. The light source layout solution that meets the threshold condition is determined as the final heat source position distribution result. By continuously adjusting the candidate positions, the system can search for a better light source layout so that the plant growth environment meets the specified satisfaction requirements.

[0086] For example, the preset satisfaction threshold is 80%. The average satisfaction of the first simulation is only 75%, which does not reach the threshold. The system adjusts the candidate positions of the light sources, performs a second round of simulation, and calculates a new average satisfaction. Repeat the iterative simulation until the average satisfaction of a simulation is 82%, which is higher than the threshold of 80%. The candidate positions of the light sources corresponding to this simulation are used as the final heat source position distribution plan.

[0087] S210: Acquire distance data from the heating light source to the target plant.

[0088] First of all, the heat-generating light source refers to a light source device that can provide both light and heat. The target plant is a plant that needs temperature control. The distance data refers to the spatial distance between the heat-generating light source and the target plant.

[0089] Specifically, after determining the position distribution of the heat-generating light sources, the system needs to know the actual distance between each light source and the target plant it is responsible for irradiating. These distance data will be used to subsequently calculate the optimal irradiation angle of the light source. Distance data can be collected through a variety of sensing devices, such as ranging sensors, depth cameras, etc. For large planting environments, it may be necessary to collect distance data from multiple points to improve accuracy. Obtaining accurate distance data is crucial for accurately calculating the irradiation angle.

[0090] For example, in a factory-based plant cultivation workshop, distance measuring sensors can be installed around the light source to monitor the vertical distance between the light source and the top of the plants below in real time; or the camera carried by a drone can be used to obtain the relative distance between the light source and all the plants.

[0091] S211, establishing a three-dimensional coordinate system according to the target environment, and mapping each of the heating light sources and the target plant corresponding to the position distribution of the heating light sources into the three-dimensional coordinate system.

[0092] First, the three-dimensional coordinate system can accurately describe the location information in the target environment. The location distribution of the heat source gives the spatial distribution scheme of the light source. Mapping refers to establishing the correspondence between two spatial information.

[0093] Specifically, after obtaining the distance data between the light source and the plant, the system needs to establish a three-dimensional coordinate system for the target environment, and then map the position of each light source in the distribution scheme and the position of the plant it illuminates to the coordinate system to obtain the accurate three-dimensional coordinates of each object. In this way, the system can calculate the light source adjustment angle based on a common coordinate system. For example, a Cartesian coordinate system with the center of the environment as the origin can be established, and then the position of each light source and plant can be converted to this coordinate system for expression. Through coordinate mapping, the system can obtain the accurate positional relationship of all objects.

[0094] S212, calculating the position vector of each target plant within the irradiation range of each heat-generating light source.

[0095] The position vector is a vector quantity used to represent the position of the target plant in the three-dimensional space coordinate system. The irradiation range of the heat source refers to the three-dimensional space area that the light emitted by the light source can reach and cover. The target plant is the plant individual that needs to be irradiated with light and temperature controlled.

[0096] Specifically, this step is to calculate the position vector of each plant relative to the light source for all target plants within the light irradiation range of each heating light source device in an environment such as a greenhouse or a plant factory. The position vector can accurately represent the position coordinate information of the target plant in the three-dimensional coordinate system. The calculation method can be: first, based on the three-dimensional coordinates of each plant and each heating light source that have been determined, the vector pointing from the light source to each plant is calculated by vector mathematical operations. The vector pointing from the light source to the plant is the position vector of the plant relative to the light source. For example, assuming that the coordinates of a heating light source are (0, 0, 0) and the three-dimensional coordinates of a target plant A are (1, 2, 3), the position vector pointing from the light source to plant A can be calculated as (1, 2, 3). By looping the calculations in sequence, the position vectors of all target plants within the light irradiation range of each heating light source can be obtained.

[0097] S213, calculating the geometric center point of each target plant within the irradiation range of each heat-generating light source.

[0098] The geometric center point is a fixed three-dimensional coordinate point that represents the center position of the target plant in three-dimensional space. The irradiation range of the heating light source refers to the three-dimensional space area that the light emitted by the light source can reach. The target plant is the individual plant that needs to be illuminated and temperature controlled.

[0099] Specifically, this step is to calculate the three-dimensional spatial coordinates of the geometric center point of each target plant within the light irradiation range of each heat-generating light source in the environment. The geometric center point can represent the spatial position of the plant. The calculation method can be: first obtain the three-dimensional spatial contour information of each target plant, and then based on these contour information, calculate the geometric center of the plant contour through a computational geometry algorithm, and the three-dimensional coordinates of this geometric center are the geometric center point of the plant. For example, if the three-dimensional contour information of a target plant A is input into the calculation, the calculated geometric center coordinates are (1.5, 2.3, 3.1), then this determined three-dimensional coordinate point is the geometric center point of the plant. Repeating this calculation process can determine the geometric center point of all target plants within the irradiation range of each heat-generating light source.

[0100] S214. Calculate the vector from the heat source to the geometric center point to obtain a unit vector.

[0101] The geometric center point is the spatial center point of the target plant expressed in three-dimensional coordinates. A heat source refers to a light source device that can provide light irradiation and heat transfer. A vector is a quantity that represents the direction and magnitude relationship between two points. A unit vector is a vector with a length defined as 1, which is used to represent a standardized direction.

[0102] Specifically, this step is to calculate the vector pointing from each heat source position in the environment to the geometric center point of each target plant within its irradiation range, and convert the calculated vector into a unit vector through mathematical operations. The calculation method is: according to the three-dimensional coordinates of the heat source and the three-dimensional coordinates of the geometric center point of the target plant, vector mathematical operations are applied to calculate the vector pointing from the light source to the geometric center point of the plant. Then the vector is normalized so that its length is 1, and the unit vector representing the direction is obtained. For example, if the coordinates of a heat source are (0, 0, 0) and the coordinates of the geometric center point of a target plant are (3, 4, 0), then the vector pointing from the light source to the center point of the plant can be calculated as (3, 4, 0), and normalization can obtain the unit vector (0.6, 0.8, 0). In this way, the unit vector removes the dimension information of the distance between the two points and only retains the direction information of the light source pointing to the plant.

[0103] S215, calculating an initial pitch angle and an initial azimuth angle of the heat-generating light source according to the unit vector, and using the initial pitch angle and the initial azimuth angle as the initial irradiation angle.

[0104] The pitch angle is the angle of the heating light source pointing up and down towards the target plant. The azimuth angle is the angle of the heating light source pointing left and right. The initial irradiation angle is the angle parameter of the heating light source that is calculated without optimization.

[0105] Specifically, this step uses the previously calculated unit vector pointing from each heating light source to the target plant, and through the calculation of coordinate transformation, calculates the initial pitch angle and initial azimuth of each light source, and uses them as the initial unoptimized irradiation angle of the light source. The calculation method is: convert or map the unit vector to a spherical coordinate system, and the resulting value is the initial pitch angle and initial azimuth of the heating light source. For example, if the calculated result of the unit vector of a light source pointing to a plant is (0.5, 0.3, 0.8), the pitch angle and azimuth results after conversion to the spherical coordinate system can be (35°, 20°), thus obtaining the initial irradiation angle parameters of the heating light source.

[0106] S216: Correct the initial irradiation angle according to the growth height of the target plant to obtain the preset irradiation angle.

[0107] Growth height refers to the expansion and change of the height of the plant during its growth. The initial irradiation angle is the unoptimized initial angle parameter of the heating light source obtained through calculation and analysis. The preset irradiation angle is the optimal angle parameter of the heating light source obtained through adjustment and optimization after considering the growth height of the target plant.

[0108] Specifically, this step is to correct and adjust the calculated initial irradiation angle of the heating light source based on the data of the growth height of the target plant, and optimize the final preset irradiation angle of the light source. During the growth cycle of the plant, its height and volume will continue to change and expand, so the irradiation angle of the light source needs to be dynamically adjusted according to the change in plant height to ensure the irradiation effect. For example, if the initial calculated irradiation angle of a heating light source is 30°, but the growth height of the target plant has increased by 10 cm in the past period of time, the system may need to adjust the initial angle to 32° based on the height change. Through the growth height correction calculation, an optimized preset irradiation angle can be obtained.

[0109] S217, controlling the heat source according to the irradiation angle.

[0110] Irradiation angle refers to the optimal irradiation angle parameter of the heating light source obtained through calculation and optimization. The heating light source is a light source device that can provide both light and heat. Control refers to the adjustment and management of the working parameters of the heating light source.

[0111] Specifically, this step is to precisely control the light source after the system obtains the optimized preset irradiation angle parameters of the heat-generating light source, so that it can work and irradiate at the calculated optimal angle. The specific control method can be: first detect the current working angle of the light source, calculate the angle that needs to be adjusted from the preset angle, and then control the motion device of the light source to perform step-by-step angle rotation until the preset optimal irradiation angle is reached; closed-loop feedback control can also be used to monitor the current working angle of the light source in real time, and continuously correct it to keep it stable at the preset optimal angle. Through precise control, the heat-generating light source can work at the most optimized angle, thereby providing plants with appropriate light irradiation and heat transfer.

[0112] S218. Monitor the temperature change and light intensity change of the environmental grid unit.

[0113] The environmental grid unit is a unit area that divides the entire target plant growth environment into multiple three-dimensional virtual grids. Temperature change refers to the increase or decrease in temperature in the environmental grid unit over time. Light intensity change refers to the increase or decrease in light intensity in the environmental grid unit over time.

[0114] Specifically, this step is to monitor the changes in temperature and light intensity values ​​in each environmental grid unit in real time. Temperature changes can be collected by setting a temperature detector in each grid unit. Light intensity changes can be collected by setting an illuminance meter in each grid unit. The monitored temperature change data and light intensity change data are both important feedback bases for evaluating the impact of light source control on the environment. For example, the current temperature value and light intensity value in each grid unit can be collected once every minute, and compared with the previous collected value, and the change amount can be calculated to continuously monitor the changing trend of temperature and light intensity in each grid unit.

[0115] S219, calculating the actual heat supply in the environmental grid unit according to the temperature change, and calculating the actual light supply in the environmental grid unit according to the light intensity change.

[0116] The actual heat supply refers to the actual heat provided by the light source in the environmental grid unit. The actual light supply refers to the actual amount of light received by the environmental grid unit.

[0117] Specifically, this step is to calculate the actual heat supply and the actual light supply provided by the light source in each grid unit through the temperature change data and light change data in each environmental grid unit that have been monitored. For example, if the temperature in a grid unit is monitored to have risen by 2°C, it can be calculated that the actual heat supply in the grid unit has increased by X joules; if the light intensity in a grid unit has increased by 500 lux, it can be calculated that the actual light supply in the grid unit has increased by Y lumens. In this way, the actual temperature control effect and light supply effect of the light source on each grid unit can be evaluated.

[0118] S220, comparing the actual heat supply with the heat demand to obtain a heat deviation value, and comparing the actual light supply with the light demand to obtain a light deviation value.

[0119] The actual heat supply refers to the actual amount of heat provided by the light source in the environmental grid cell. The heat demand refers to the heat conditions required by the plant in the grid cell. The actual light supply refers to the actual amount of light received in the environmental grid cell. The light demand refers to the amount of light required by the plant in the grid cell. The heat deviation value and light deviation value are the difference between the actual supply value and the demand value, respectively.

[0120] Specifically, this step is to compare the calculated actual heat supply value of the light source in each environmental grid unit with the heat demand value of the plant in the grid unit, and calculate the difference between the two, that is, the heat deviation value; at the same time, compare the actual light supply value in each grid unit with the light demand value of the plant, and calculate the difference between the two, that is, the light deviation value. For example, if the actual heat supply in an environmental grid unit is calculated to be 80 joules, but the heat demand of the plant in the grid unit is 100 joules, then the heat deviation value of the grid unit is -20 joules; if the light demand in a grid unit is 1000 lux, but the actual light supply is only 800 lux, then the light deviation value of the grid unit is -200 lux.

[0121] S221: When the heat deviation value or the light deviation value exceeds a preset threshold, the power of the heat source is adjusted to a preset power.

[0122] The preset threshold refers to the maximum range of the heat deviation value or light deviation value allowed by the system. Adjusting the power refers to changing the working power of the heating light source. The preset power is the target working power value of the heating light source obtained through optimization calculation.

[0123] Specifically, this step is to determine whether the heat deviation value or light deviation value in the environmental grid unit exceeds the maximum allowable threshold value preset by the control system. If it exceeds the threshold value, the working electric power of the heat source corresponding to the grid unit is increased or decreased to control the power of the light source to reach the optimal target power value obtained by the system optimization calculation. For example, if the heat deviation of a grid unit exceeds the maximum allowable value of 10 joules, the power of the light source corresponding to the grid unit is increased; if the light deviation of a grid unit exceeds the maximum allowable value of 100 lux, the power of the corresponding light source is reduced. In this way, the output parameters of each light source can be adjusted in time, so that the actual light and heat supply in each grid unit is as close as possible to the needs of the plants.

[0124] S222: When the heat deviation value or the light deviation value exceeds a maximum threshold, a prompt message is sent to the target client.

[0125] The maximum threshold refers to the maximum allowable range threshold of the heat deviation value and light deviation value preset by the low-heat light source control system. The prompt information refers to the reminder notification information sent by the system when the heat or light deviation exceeds the threshold. The target client refers to the user-end device or interface that receives the prompt information.

[0126] Specifically, this step is to determine whether the heat deviation value or light deviation value in the environmental grid unit has exceeded the maximum allowable threshold preset in the control system. If any deviation exceeds the range of its corresponding maximum threshold, the low-heat light source control system will immediately and actively send a prompt notification message to the user end to remind the user that there is a problem with the current environmental control status. For example, when the light deviation value in a grid unit has exceeded the preset maximum allowable threshold of 500 lux, the system will send a prompt message of "The current light supply is abnormal, please check the relevant light source equipment" to the user interface of the environmental monitoring platform to remind the user that the light supply is abnormal. When the deviation exceeds the maximum allowable range, the prompt message is actively sent, so that the system user can understand the current environmental control problem in a timely manner so that corresponding update and adjustment measures can be taken.

[0127] S223: Compare the current image of the target plant with the historical image of the target plant to obtain the change rate of the target plant.

[0128] The current image refers to the most recently acquired image of the target plant. The historical image refers to the image of the target plant acquired at a certain growth stage in the past. The rate of change can indicate the degree of growth change of the target plant between different growth stages.

[0129] Specifically, this step uses image processing and computer vision technology to select the current image of the target plant and the image of the historical growth stage, perform comparative analysis, calculate the difference between the two images, and finally obtain the growth change rate of the target plant. For example, you can select the seed stage image and the flowering stage image of the same plant for comparison, and by analyzing the changes in the plant size, color, morphology, etc. in the two-stage images, you can get a quantitative change rate curve representing the growth rate of the plant.

[0130] S224: Send the change rate to the target client.

[0131] The change rate is a plant growth change index calculated by comparing the current image and the historical image of the target plant. The target client is the user-side system or device that needs to obtain the plant growth status.

[0132] Specifically, this step is to send the obtained image change rate data of the target plant to the user-side system so that the user can understand the growth status of the plant. The sending method can be that the system background sends the data in json or xml format to the front-end user interface in the form of an API interface through a network interface; or a socket long connection can be established to push the change rate data to the user terminal in real time. After receiving the change rate data, the user client can visualize it to form a growth rate monitoring report or control panel, intuitively presenting the growth status of the plant, and facilitate users to evaluate the current light and temperature control effects, so as to better manage the plant growth environment.

[0133] The following describes the low-heat light source control system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of a physical device structure of a low-heat light source control system in an embodiment of the present application.

[0134] It should be noted that Figure 3 The structure of the low-heat light source control system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0135] like Figure 3As shown, the low-heat light source control system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0136] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0137] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0138] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0139] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0140] Specifically, the low-heat light source control system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the low-heat light source control method suitable for plant growth provided in the above embodiment is implemented.

[0141] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the low-heat light source control system described in the above embodiment; or may exist independently without being assembled into the low-heat light source control system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the low-heat light source control system, the low-heat light source control system implements the low-heat light source control method suitable for plant growth provided in the above embodiment.

[0142] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0143] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0144] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A low-heat light source control method suitable for plant growth, characterized in that: Applied to a low-heat light source control system, the method comprises: Collecting current environmental data in a target environment, plant type data of a target plant, and thermal distribution data in the target environment, wherein the target environment includes a plurality of the target plants; Inputting the plant type data into a plant growth cycle model to obtain the heat demand and light demand of the target plant at each preset growth stage; Calculate and generate the heat source position distribution according to the heat demand, the light demand and the thermal distribution data; Acquire distance data from the heating light source to the target plant; Determining a preset irradiation angle of the heating light source according to the position distribution of the heating light source and the distance data; The heat-generating light source is controlled according to the irradiation angle.

2. The method according to claim 1, characterized in that The step of calculating and generating the heat source position distribution according to the heat demand, the light demand and the thermal distribution data specifically includes: Dividing the target environment into a plurality of environmental grid units, and calculating actual heat data of each of the environmental grid units according to the thermal distribution data; Calculating the heat regulation requirement of each of the environmental grid units according to the heat requirement and the actual heat data; Calculating a comprehensive requirement of each of the environmental grid cells according to the heat regulation requirement and the lighting requirement; Simulating candidate locations of heat-generating light sources in the target environment, and obtaining simulated heat and simulated light intensity of each grid cell of the environment; Calculate the average satisfaction of all the environmental grid cells according to the simulated heat, the simulated light and the comprehensive demand; Repeat the step of simulating candidate positions of heating light sources in the target environment so that the average satisfaction is greater than a preset satisfaction threshold, and use the obtained simulated heating light source candidate positions greater than the preset satisfaction threshold as the heating light source position distribution.

3. The method according to claim 1, characterized in that The step of determining the preset irradiation angle of the heating light source according to the position distribution of the heating light source and the distance data specifically includes: Establishing a three-dimensional coordinate system according to the target environment, and mapping each of the heat-generating light sources and the target plant corresponding to the position distribution of the heat-generating light sources into the three-dimensional coordinate system; Calculate the position vector of each target plant within the irradiation range of each heat-generating light source; Calculating an initial irradiation angle of each of the heat-generating light sources according to the position distribution of each of the target plants within the irradiation range; The initial irradiation angle is corrected according to the growth height of the target plant to obtain the preset irradiation angle.

4. The method according to claim 3, characterized in that The step of calculating the initial irradiation angle of each of the heat-generating light sources according to the position distribution of each of the target plants within the irradiation range specifically includes: Calculating the geometric center point of each of the target plants within the irradiation range of each of the heat-generating light sources; Calculate the vector from the heat source to the geometric center point to obtain a unit vector; An initial pitch angle and an initial azimuth angle of the heat-generating light source are calculated according to the unit vector, and the initial pitch angle and the initial azimuth angle are used as the initial irradiation angle.

5. The method according to claim 1, characterized in that After the step of controlling the heat-generating light source according to the irradiation angle, the method further includes: Monitoring temperature changes and light intensity changes of environmental grid cells, wherein the environmental grid cells are obtained by dividing the target environment into a plurality of environmental grid cells; Calculating the actual heat supply in the environmental grid unit according to the temperature change, and calculating the actual light supply in the environmental grid unit according to the light intensity change; Compare the actual heat supply with the heat demand to obtain a heat deviation value, and compare the actual light supply with the light demand to obtain a light deviation value; When the heat deviation value or the light deviation value exceeds a preset threshold, the power of the heat source is adjusted to a preset power.

6. The method according to claim 5, characterized in that After the steps of comparing the actual heat supply with the heat demand to obtain a heat deviation value, and comparing the actual light supply with the light demand to obtain a light deviation value, the method further includes: When the heat deviation value or the light deviation value exceeds a maximum threshold, a prompt message is sent to the target client.

7. The method according to claim 6, characterized in that After the step of sending a prompt message to the target client when the heat deviation value or the light deviation value exceeds a maximum threshold, the method further includes: Comparing the current image of the target plant with the historical image of the target plant to obtain the change rate of the target plant; The change rate is sent to the target client.

8. A low heat source control system, characterized in that: The low-heat light source control system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the low-heat light source control system to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a low-heat light source control system, the low-heat light source control system is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product runs on a low-heat-generating light source control system, the low-heat-generating light source control system is enabled to perform the method according to any one of claims 1 to 7.

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