Tea garden intelligent management and control system integrated with environment monitoring

Abstract

The invention provides a tea garden intelligent management and control system integrated with environmental monitoring, and the system comprises a monitoring module which comprises a meteorological environment monitoring sensor, a soil environment monitoring sensor and a camera, the meteorological environment monitoring sensor is used for monitoring meteorological data, and the meteorological data comprises atmospheric temperature, atmospheric humidity, illumination intensity and wind speed; the soil environment monitoring sensor is used for monitoring soil data, and the soil data comprises soil temperature, soil humidity, soil conductivity and soil pH value; the camera is used for shooting tea images; the task processing module comprises a tea visual identification module which is used for processing the tea based on a deep learning tea identification model so as to identify the number of tea buds which can be picked in a unit area, and further estimating the yield; the tea garden insect pest prediction model is used for predicting insect pest occurrence probabilities and hazard levels at different time points by adopting a tea garden insect pest disaster formation prediction model based on time sequence prediction on the basis of the meteorological data and the soil data; according to the insect pest adaptive water, fertilizer and liquid medicine proportioning optimization model, the proportions of water, fertilizer and liquid medicine required at different time points are obtained according to different growth stages and insect pest hazard grades of the tea trees.

Description

Technical Field

[0001] This invention relates to the field of intelligent tea garden management, and in particular to an intelligent tea garden control system that integrates environmental monitoring. Background Technology

[0002] Current tea garden management faces prominent challenges, including vast areas, complex terrain, high labor costs, and low efficiency of manual management. Traditional manual inspections and experience-based management methods are not only labor-intensive and suffer from delayed information feedback, but also struggle to detect pests and water imbalances in a timely manner, leading to significant fluctuations in tea yield and quality. To improve management precision and production efficiency, information and intelligent technologies are gradually being introduced into tea cultivation, forming a preliminary intelligent control system. Existing technologies mainly focus on the intelligent transformation of single aspects, such as using remote sensing, geographic information systems, and data analysis to achieve tea garden site selection and ecological suitability assessment, or using automatic irrigation systems based on temperature, humidity, light, and soil moisture sensors to control water and fertilizer supply according to thresholds to improve resource utilization. However, these systems generally suffer from functional fragmentation, information isolation, and incomplete decision-making chains, making it difficult to achieve intelligent management of tea gardens. Furthermore, given the uncertainty of pest occurrences and the differences in tea tree growth stages, existing systems lack the ability to adaptively adjust water, fertilizer, and pesticide ratios, failing to achieve dynamic and precise management of tea garden production. Therefore, it is necessary to develop an intelligent control system that integrates environmental monitoring and adaptive decision control to achieve intelligent management of tea gardens. Summary of the Invention

[0003] The main objective of this invention is to provide an intelligent management and control system for tea gardens that integrates environmental monitoring, enabling automatic management and control of tea gardens.

[0004] To achieve the above objectives, the technical solution adopted by this invention is: an intelligent tea garden management and control system integrating environmental monitoring, comprising: The monitoring module includes a meteorological environment monitoring sensor, a soil environment monitoring sensor, and a camera. The meteorological environment monitoring sensor is used to monitor meteorological data, including atmospheric temperature, atmospheric humidity, light intensity, and wind speed. The soil environment monitoring sensor is used to monitor soil data, including soil temperature, soil humidity, soil electrical conductivity, and soil pH. The camera is used to capture images of tea leaves. The task processing module includes: The tea visual recognition module processes the tea image based on a deep learning-based tea recognition model to identify the number of harvestable tea buds within a unit area, thereby estimating the yield. The tea garden pest prediction module predicts the probability of pest occurrence and the level of damage at different time points based on the tea images. A soil drought prediction model is used to predict soil drought conditions based on the meteorological and soil data. The pest-adaptive water, fertilizer, and pesticide solution ratio optimization module obtains the required types of water, fertilizers, pesticide solutions, and application amounts based on different growth stages of tea trees, the probability and severity of pest occurrences, and drought conditions.

[0005] Preferably, it also includes a control module for receiving the estimated yield, drought conditions, and required types of water, fertilizer, and pesticide solutions, as well as their ratios and application rates, output by the task processing module, and generating execution instructions. The execution instructions include harvesting instructions and pesticide / fertilizer spraying instructions: when the yield prediction reaches the harvesting standard, a harvesting instruction is issued; when the drought reaches a certain level or the pest infestation reaches a certain severity, a pesticide / fertilizer spraying instruction is executed. The pesticide / fertilizer spraying instruction contains instructions corresponding to the required types of water, fertilizer, pesticide solutions, their ratios, and application rates.

[0006] Preferably, it also includes an execution module for performing corresponding operations according to the instructions generated by the control module. The execution module includes tea picking equipment and pesticide spraying and irrigation equipment. When a picking instruction is received, the picking equipment is driven to pick tea in a designated area. When a pesticide spraying instruction is received, pesticide spraying and irrigation are performed according to the required types of water and fertilizer, types and ratios of pesticides and fertilizers, and application amounts.

[0007] Preferably, the spraying and irrigation equipment includes multiple mother liquor inlet pipes, clean water inlet pipes, mixing chambers, and mixed solution outlet pipes for inputting different pesticides or fertilizer solutions. Different pesticides or fertilizers are input into the mixing chamber through the corresponding mother liquor inlet pipes, and clean water is input into the mixing chamber through the clean water inlet pipes. Different pesticides or fertilizers are mixed with clean water in the mixing chamber in a predetermined ratio, and then output to the tea garden through the mixed solution outlet pipes.

[0008] Preferably, the flow rates of different chemicals or fertilizers and water in the mother liquor inlet pipeline and the clean water inlet pipeline are calculated using the following steps: Step 1: Optimization Model for Pest-Adaptive Water-Fertilizer-Pesticide Mixture Ratio. The target concentration of different pesticide or water-fertilizer solutions in the output solution is obtained using the following formula. : (1), in, To output the concentration of the i-th type of mother liquor in the solution, where the mother liquor can be different medicinal solutions or different fertilizers. This indicates the basic concentration of the i-th type of mother liquor or the basic fertilizer concentration at this growth stage of the tea plant. and These are the predicted values ​​and thresholds for the severity of pest infestations. Let be the insect pest response function for the i-th type of mother liquor. and Compensation coefficient and inhibition coefficient, respectively; Step 2: According to the mass conservation equation, we get: (2), in, Indicates the volume of the mixing chamber. and Let represent the concentration and flow rate of the i-th type of mother liquor in the mother liquor input pipeline, respectively. This indicates the concentration of the i-th type of mother liquor in the mixed solution output pipeline. The flow rate of the aqueous solution in the mixed solution output pipeline is equal to the sum of the flow rates of each mother liquor input and the flow rate of the clean water. Step 3: When the input and output within the mixing chamber reach equilibrium, that is... That is, we get: (3); Step 4: Concentration in the mother liquor output pipeline equal to target concentration Therefore, we can obtain: (4), (5), in, To control the target output flow rate of each mother liquor input pipeline, The target output flow rate for the clean water input pipeline.

[0009] Preferably, a water pump is installed in each mother liquor input pipeline and each clean water input pipeline. The target output flow rate is controlled by controlling the water pumps. The water pump control adopts PID control, and the control is carried out in the following steps: Step a: The control method for each water pump is represented using a first-order system, with the transfer function as follows: (6), in, This is the control command for the water pump in the i-th mother liquor input pipeline. The static gain of the control command for the water pump in the i-th mother liquor input pipeline is used to represent the sensitivity. Let be the delay constant of the control command for the water pump in the i-th mother liquor input pipeline; This indicates the response speed of the control command for the water pump in the i-th mother liquor input pipeline; Step b: By using the first-order Pad approximation to process the hysteresis element, the parameter tuning of the PI controller is obtained, as follows: (7), (8), in, The proportional gain of the control command for the water pump in the i-th mother liquor input pipeline; The integral time of the control command for the water pump in the i-th mother liquor input pipeline; Let be the closed-loop time constant of the control command for the water pump in the i-th mother liquor input pipeline; Step c: Obtain control commands based on formulas (7) and (8). : (9), (10) (11), in, For error, Let represent the static characteristic of the i-th pump, and let represent the nonlinear relationship between the control command and the flow rate.

[0010] Compared with the prior art, the present invention has the following beneficial effects: This invention can monitor multiple data points in a tea garden through a monitoring module. The acquired data can determine whether the tea leaves are ready for harvest, whether there are pests, and whether irrigation is needed. It can also automatically harvest, apply pesticides, fertilize, and irrigate, and in particular, it can achieve simultaneous application of pesticides, fertilizers, and irrigation. Attached Figure Description

[0011] Figure 1 This is a block diagram of the intelligent control system according to the present invention. Detailed Implementation

[0012] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0013] A smart tea garden management and control system integrating environmental monitoring includes a monitoring module, a control module, an execution module, a task processing module, and a network communication module.

[0014] The monitoring module includes a meteorological environment monitoring sensor, a soil environment monitoring sensor, and a camera. The meteorological environment monitoring sensor monitors meteorological data, including atmospheric temperature, atmospheric humidity, light intensity, and wind speed. The soil environment monitoring sensor monitors soil data, including soil temperature, soil moisture, soil electrical conductivity, and soil pH. The camera captures images of tea leaves. The network communication module enables communication between the various modules.

[0015] The task processing module includes a tea leaf visual recognition module, a tea garden pest prediction module, a soil drought prediction model, and a pest-adaptive water, fertilizer, and pesticide ratio optimization module. The visual recognition module processes the tea leaves using a deep learning-based tea leaf recognition model to identify the number of harvestable tea buds per unit area, thereby estimating the yield. The pest prediction module predicts the probability of pest occurrence and the severity of damage at different time points based on the tea leaf images. The soil drought prediction model is used to predict soil drought conditions based on the meteorological and soil data. The pest-adaptive water, fertilizer, and pesticide ratio optimization module obtains the required types of water, fertilizer, pesticides, and pesticides, as well as their ratios and application rates, based on different growth stages of the tea trees, the probability and severity of pest occurrence, and the drought conditions. It then outputs combined sprinkler irrigation and control instructions to achieve integrated water, fertilizer, and pest control.

[0016] The control module receives the estimated yield, drought conditions, and required types of water, fertilizer, and pesticide solutions, as well as their ratios and application rates, from the task processing module and generates execution instructions. These instructions include harvesting instructions and pesticide / fertilizer spraying instructions: when the yield prediction reaches the harvesting standard, a harvesting instruction is issued; when the drought reaches a certain level or the pest infestation reaches a certain severity, a pesticide / fertilizer spraying instruction is executed. This instruction contains the required types of water and fertilizer, pesticide solutions, their ratios, and application rates.

[0017] The execution model is used to perform corresponding operations according to the instructions generated by the control module, which includes tea picking equipment and pesticide spraying and irrigation equipment. When a picking instruction is received, the picking equipment is driven to pick tea in a designated area; when a pesticide spraying instruction is received, pesticide spraying and irrigation are performed according to the required types of water and fertilizer, pesticide types and ratios, and application rates.

[0018] The spraying and irrigation equipment includes multiple mother liquor inlet pipes, clean water inlet pipes, mixing chambers, and mixed solution outlet pipes for inputting different pesticides or fertilizer solutions. Different pesticides or fertilizers are input into the mixing chamber through the corresponding mother liquor inlet pipes, and clean water is input into the mixing chamber through the clean water inlet pipes. Different pesticides or fertilizers are mixed with clean water in the mixing chamber in a predetermined ratio, and then output to the tea garden through the mixed solution outlet pipes.

[0019] Specifically, the flow rates of different chemicals or fertilizers and clean water in the mother liquor inlet pipeline and the clean water inlet pipeline are calculated using the following steps: Step 1: Optimization Model for Pest-Adaptive Water-Fertilizer-Pesticide Mixture Ratio. The target concentration of different pesticide or water-fertilizer solutions in the output solution is obtained using the following formula. : (1), in, This outputs the concentration of the i-th type of mother liquor in the solution, where the mother liquor is either a medicinal solution or a fertilizer, and the fertilizer is a solution. This indicates the basic fertilizer concentration of the i-th type of mother liquor at this growth stage of the tea plant. and These are the predicted values ​​and thresholds for the severity of pest infestations. Let be the insect pest response function for the i-th type of mother liquor. Using existing technology, and Compensation coefficient and inhibition coefficient, respectively; Step 2: According to the mass conservation equation, we get: (2), in, Indicates the volume of the mixing chamber. and Let represent the concentration and flow rate of the i-th type of mother liquor in the mother liquor input pipeline, respectively. This indicates the concentration of the i-th type of mother liquor in the mixed solution output pipeline. The flow rate in the mixed solution output pipeline is equal to the sum of the input flow rates of each mother liquor and the flow rate of the clean water. Step 3: When the input and output within the mixing chamber reach equilibrium, that is... That is, we get: (3); Step 4: Concentration in the mother liquor output pipeline equal to target concentration Therefore, we can obtain: (4), (5), in, To control the target output flow rate of each mother liquor input pipeline, The target output flow rate for the clean water input pipeline.

[0020] A water pump is installed on each mother liquor input pipeline and each clean water input pipeline. The target output flow rate is controlled by controlling the water pumps. The water pumps are controlled using PID control, and the specific control steps are as follows: Step a: The control method for each water pump is represented using a first-order system, with the transfer function as follows: (6), in, This is the control command for the water pump in the i-th mother liquor input pipeline. The static gain of the control command for the water pump in the i-th mother liquor input pipeline is used to represent the sensitivity. Let be the delay constant of the control command for the water pump in the i-th mother liquor input pipeline; This indicates the response speed of the control command for the water pump in the i-th mother liquor input pipeline; Step b: By using the first-order Pad approximation to process the hysteresis element, the parameter tuning of the PI controller is obtained, as follows: (7), (8), in, The proportional gain of the control command for the water pump in the i-th mother liquor input pipeline; The integral time of the control command for the water pump in the i-th mother liquor input pipeline; Let be the closed-loop time constant of the control command for the water pump in the i-th mother liquor input pipeline; Step c: Obtain control commands based on formulas (7) and (8). : (9), (10) (11), in, For error, Let represent the static characteristic of the i-th pump, and let represent the nonlinear relationship between the control command and the flow rate.

[0021] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart management and control system for tea gardens integrating environmental monitoring, characterized in that, include: The monitoring module includes a meteorological environment monitoring sensor, a soil environment monitoring sensor, and a camera. The meteorological environment monitoring sensor is used to monitor meteorological data, including atmospheric temperature, atmospheric humidity, light intensity, and wind speed. The soil environment monitoring sensor is used to monitor soil data, including soil temperature, soil humidity, soil electrical conductivity, and soil pH. The camera is used to capture images of tea leaves. The task processing module includes: The tea visual recognition module processes the tea image based on a deep learning-based tea recognition model to identify the number of harvestable tea buds in a unit area, thereby estimating the yield. The tea garden pest prediction module predicts the probability of pest occurrence and the level of damage at different time points based on the tea leaf images. A soil drought prediction model is used to predict soil drought conditions based on the meteorological and soil data. The pest-adaptive water, fertilizer, and pesticide solution ratio optimization module obtains the required types of water, fertilizers, pesticide solutions, and application amounts based on different growth stages of tea trees, the probability and severity of pest occurrences, and drought conditions.

2. The intelligent tea garden management and control system integrating environmental monitoring according to claim 1, characterized in that, It also includes a control module, which receives the estimated yield, drought conditions, and required types of water, fertilizer, and pesticide solutions, as well as their ratios and application rates, from the task processing module and generates execution instructions. The execution instructions include harvesting instructions and pesticide / fertilizer spraying instructions: when the yield prediction reaches the harvesting standard, a harvesting instruction is issued; when the drought reaches a certain level or the pest infestation reaches a certain severity, a pesticide / fertilizer spraying instruction is executed. The pesticide / fertilizer spraying instruction contains instructions corresponding to the required types of water, fertilizer, pesticide solutions, their ratios, and application rates.

3. The intelligent tea garden management and control system integrating environmental monitoring according to claim 1, characterized in that, It also includes an execution module, which is used to perform corresponding operations according to the instructions generated by the control module. The execution module includes tea picking equipment and pesticide spraying and irrigation equipment. When a picking instruction is received, the picking equipment is driven to pick tea in a designated area. When a pesticide spraying instruction is received, the pesticide spraying and irrigation are performed according to the required water, fertilizer type, pesticide type and ratio and application amount.

4. The intelligent tea garden management and control system integrating environmental monitoring according to claim 3, characterized in that, The spraying and irrigation equipment includes multiple mother liquor inlet pipes, clean water inlet pipes, mixing chambers, and mixed solution outlet pipes for inputting different pesticides or fertilizer solutions. Different pesticides or fertilizers are input into the mixing chamber through the corresponding mother liquor inlet pipes, and clean water is input into the mixing chamber through the clean water inlet pipes. Different pesticides or fertilizers are mixed with clean water in the mixing chamber in a predetermined ratio, and then output to the tea garden through the mixed solution outlet pipes.

5. The intelligent tea garden management and control system integrating environmental monitoring according to claim 4, characterized in that, The flow rates of different chemical solutions or fertilizer solutions, as well as water, in the mother liquor inlet pipeline and the clean water inlet pipeline are calculated using the following steps: Step 1: Optimization Model for Pest-Adaptive Water-Fertilizer-Pesticide Mixture Ratio. The target concentration of different pesticide or water-fertilizer solutions in the output solution is obtained using the following formula. : （1）， in, To output the concentration of the i-th type of mother liquor in the solution. This indicates the basic fertilizer concentration of the i-th type of mother liquor at this growth stage of the tea plant. and These are the predicted values ​​and thresholds for the severity of pest infestations. Let be the insect pest response function for the i-th type of mother liquor. and Compensation coefficient and inhibition coefficient, respectively; Step 2: According to the mass conservation equation, we get: （2）， in, Indicates the volume of the mixing chamber. and Let represent the concentration and flow rate of the i-th type of mother liquor in the mother liquor input pipeline, respectively. This indicates the concentration of the i-th type of mother liquor in the mixed solution output pipeline. The flow rate of the aqueous solution in the mixed solution output pipeline is equal to the sum of the flow rates of each mother liquor input and the flow rate of the clean water. Step 3: When the input and output within the mixing chamber reach equilibrium, that is... That is, we get: （3）； Step 4: Concentration in the mother liquor output pipeline equal to target concentration Therefore, we can obtain: （4）， （5）， in, To control the target output flow rate of each mother liquor input pipeline, The target output flow rate for the clean water input pipeline.

6. The intelligent tea garden management and control system integrating environmental monitoring according to claim 5, characterized in that, A water pump is installed on each mother liquor input pipeline and each clean water input pipeline. The target output flow rate is controlled by controlling the water pumps. The water pumps are controlled using PID control, and the specific control steps are as follows: Step a: The control method for each water pump is represented using a first-order system, with the transfer function as follows: （6）， in, This is the control command for the water pump in the i-th mother liquor input pipeline. The static gain of the control command for the water pump in the i-th mother liquor input pipeline is used to represent the sensitivity. Let be the delay constant of the control command for the water pump in the i-th mother liquor input pipeline; This indicates the response speed of the control command for the water pump in the i-th mother liquor input pipeline; Step b: By using the first-order Pad approximation to process the hysteresis element, the parameter tuning of the PI controller is obtained, as follows: （7）， （8）， in, The proportional gain of the control command for the water pump in the i-th mother liquor input pipeline; The integral time of the control command for the water pump in the i-th mother liquor input pipeline; Let be the closed-loop time constant of the control command for the water pump in the i-th mother liquor input pipeline; Step c: Obtain control commands based on formulas (7) and (8). : （9）， （10）， （11）， in, For error, This represents the static characteristics of the actuator, indicating the nonlinear relationship between control commands and flow rate.

Images