Chinese herbal medicine cultivation system

Abstract

The invention relates to the technical field of Chinese herbal medicine cultivation, in particular to a Chinese herbal medicine cultivation system which comprises an environment monitoring and regulation module, a health monitoring and early warning module, an intelligent scheduling and response module and a data analysis module. The environment monitoring and regulation module monitors environment parameters in a cultivation environment in real time; the health monitoring and early warning module monitors health conditions of Chinese herbal medicines in real time and analyzes diseases and insect pests or nutrition problems; the intelligent scheduling and response module optimizes resources of a cultivation environment; the data analysis module analyzes the growth trend and environmental adaptability of the Chinese herbal medicines based on the optimized growth conditions and cultivation environment resources of the Chinese herbal medicines, and generates cultivation suggestions; according to the method, corresponding measures can be identified and taken as early as possible, so that the outbreak of plant diseases and insect pests is avoided or reduced, and the growth quality and yield of plants are optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of Chinese herbal medicine cultivation, and particularly to a Chinese herbal medicine cultivation system. Background Art

[0002] Chinese herbal medicine cultivation plays an important role in modern agriculture. Especially with the increasing attention of people to health and natural therapies, the demand for Chinese herbal medicines is growing continuously. In order to improve the planting efficiency and quality of Chinese herbal medicines, how to provide the most suitable growth environment for plants has become the focus of cultivation technology research. Traditional Chinese herbal medicine cultivation mostly relies on manual management, which is cumbersome and inefficient, and it is difficult to accurately adjust environmental conditions, especially in terms of temperature and humidity control, light management, and soil nutrient regulation, and cannot respond in a timely manner according to real-time data.

[0003] At present, although some advanced agricultural technologies have begun to introduce automated management means, in the field of Chinese herbal medicine cultivation, the application of related technologies still has many deficiencies. Most of the existing cultivation systems focus on the monitoring of single factors, such as temperature and humidity control or pest control, and lack a comprehensive integrated system that cannot comprehensively manage the cultivation environment in multiple dimensions. At the same time, the existing intelligent cultivation technologies are mostly limited to simple data collection and processing, lacking in-depth analysis and automatic adjustment functions for plant health conditions, especially in aspects such as plant root and leaf growth and pest warning. The monitoring results have not been effectively transformed into actual scheduling actions. Such systems have insufficient analysis of environmental adaptability and cannot adjust the allocation of cultivation resources according to the different growth stages and specific needs of Chinese herbal medicine growth.

[0004] In view of the deficiencies of the prior art, the present invention proposes an intelligent Chinese herbal medicine cultivation system that can provide continuous cultivation suggestions, realize the optimal allocation of cultivation resources, thereby improving the production efficiency of Chinese herbal medicine cultivation, reducing manual intervention, and meeting the needs of different growth stages. Summary of the Invention

[0005] The present invention provides a Chinese herbal medicine cultivation system to solve the technical problems mentioned in the background art part;

[0006] A Chinese herbal medicine cultivation system includes an environmental monitoring and regulation module, a health monitoring and warning module, an intelligent scheduling and response module, and a data analysis module, wherein;

[0007] The environmental monitoring and regulation module monitors the environmental parameters in the cultivation environment in real time, including temperature, humidity, light intensity, soil pH value, and nutrient content, and optimizes the growth conditions of Chinese herbal medicines by adjusting the environmental parameters;

[0008] The health monitoring and early warning module monitors the health status of Chinese herbal medicines in real time, including root development, leaf growth, and signs of pests and diseases, and analyzes pest or nutritional problems based on the monitoring results of the health status;

[0009] The intelligent scheduling and response module optimizes the resources of the cultivation environment, including irrigation, fertilization, and pest control, based on the analysis results of pest or nutritional problems;

[0010] The data analysis module analyzes the growth trend and environmental adaptability of Chinese herbal medicines based on the optimized growth conditions of Chinese herbal medicines and the resources of the cultivation environment, and generates cultivation suggestions.

[0011] Optionally, the environment monitoring and regulation module includes:

[0012] Environmental parameter collection: Real-time monitoring of temperature, humidity, light intensity, soil pH, and nutrient content in the cultivation environment through a variety of sensors;

[0013] Temperature and humidity regulation: According to the real-time monitored temperature T real and humidity H real as well as the target temperature T set and target humidity H set , calculate the temperature and humidity deviation and automatically adjust the heating and humidification systems in the cultivation environment;

[0014] Light intensity regulation: According to the real-time monitored light intensity L real and the preset target light intensity L set , calculate the light deviation and adjust the artificial light source in the cultivation area;

[0015] Soil pH and nutrient content regulation: According to the monitored soil pH real and nutrient content N real and the preset target soil pH set and target nutrient content N set , calculate the soil pH and nutrient content deviation and automatically control the soil adjustment equipment (such as pH regulators or fertilization systems) to adjust the soil pH and nutrients to the optimal range.

[0016] Optionally, the health monitoring and early warning module includes:

[0017] Plant health monitoring: Real-time monitoring of the health status of Chinese herbal medicines through sensors and image recognition technology, including root development, leaf growth, and signs of pests and diseases;

[0018] Health status analysis: Based on the monitored health status of Chinese herbal medicines, predict the outbreak risk of pests and diseases. At the same time, analyze whether Chinese herbal medicines lack key nutrients (nitrogen, phosphorus, potassium), and predict whether there are malnutrition problems in Chinese herbal medicines.

[0019] Optionally, the plant health monitoring includes:

[0020] Root development monitoring: By X-ray scanning the image data of the roots, identify whether there are problems of root rot or stunted growth;

[0021] Leaf growth monitoring: Measure the greenness and chlorophyll content of the leaves through a spectral sensor (NDVI), capture the leaf image data through a camera, identify the growth status of the leaves, including chlorosis and wilting problems, and monitor the leaf temperature through a leaf temperature sensor;

[0022] Pest and disease sign monitoring: By taking the image data of the leaves and stems through a camera, monitor the signs of pests and diseases, including insect holes, spots, and withering and yellowing.

[0023] Optionally, the health condition analysis includes:

[0024] Pest and disease sign analysis: Based on the monitored health condition of the Chinese herbal medicine, use a convolutional neural network (CNN) model to extract the pest and disease sign features of the roots, leaves, and stems, including the damaged area, morphological features, and texture features, and calculate the damage score, indicating the degree of pests and diseases of the Chinese herbal medicine;

[0025] Malnutrition prediction: Collect the key nutrient elements of the soil, including nitrogen, phosphorus, and potassium content, through a soil sensor, and evaluate the degree of nutrient deficiency N in combination with the standard nutrient content required by the Chinese herbal medicine deficiency .

[0026] Optionally, the pest and disease sign analysis includes:

[0027] Feature extraction: Use a convolutional neural network (CNN) model to analyze the image data of the collected roots, leaves, and stems, and extract the features F of the pest and disease signs out , including the damaged area, morphological features, and texture features;

[0028] Damage score calculation: Based on the output F of the convolutional neural network (CNN) model out , calculate the damage score I damage , reflecting the degree of pests and diseases, ranging from 0 to 1, where 0 represents complete health and 1 represents severe damage;

[0029] Pest and disease degree judgment: According to the damage score I damage , divide the degree of pests and diseases of the Chinese herbal medicine into multiple levels. When 0 ≤ I damage < 0.2, it represents the healthy state. When 0.2 ≤ I damage < 0.5, it represents mild damage. When 0.5 ≤ I damage < 0.8, it represents moderate damage. When 0.8 ≤ Idamage When it is ≤ 1, it indicates severe damage.

[0030] Optionally, the intelligent scheduling and response module includes:

[0031] Scheduling resource judgment: Based on the calculated degree of nutrient deficiency N deficiency , combined with the result of the judgment of the degree of pests and diseases, determine whether resource scheduling is required;

[0032] Resource optimization decision-making: Use an optimization algorithm to optimize the resource allocation in the cultivation environment, including irrigation, fertilization, and pest and disease control.

[0033] Optionally, the scheduling resource judgment includes:

[0034] No resource scheduling required: When I damage <0.2 and N deficiency <0.2, the degree of pests and diseases is low and the nutrients are sufficient, no resource scheduling is required. When 0.2 ≤ I damage <0.5 and N deficiency <0.2, there are minor pest and disease damages, but the nutrients are sufficient, no resource scheduling is required. When I damage <0.2 and 0.2 ≤ N deficiency <0.5, there are no problems with pests and diseases, but there is a slight lack of nutrients, no resource scheduling is required;

[0035] Optimized resource scheduling: When I damage ≥ 0.5, the pest and disease damages are severe, and optimized resource scheduling is required. When 0.2 ≤ I damage <0.5 and N deficiency ≥ 0.5, there are minor pest and disease damages, and at the same time, there is a severe lack of nutrients, and optimized resource scheduling is required. When N deficiency ≥ 0.5 and I damage <0.2, the nutrients are severely lacking, and the plant growth is restricted, and optimized resource scheduling is required.

[0036] Optionally, the data analysis module includes:

[0037] Growth trend analysis: Based on the optimized environmental parameters, use a linear regression model to predict the future growth trend of Chinese herbal medicines;

[0038] Environmental adaptability analysis: By comparing the health status of Chinese herbal medicines with changes in environmental parameters, use a support vector machine (SVM) model to analyze the environmental adaptability of Chinese herbal medicines and judge whether the cultivation environment is most suitable for the growth of current Chinese herbal medicines;

[0039] Cultivation suggestion generation: Based on the results of growth trend analysis and environmental adaptability analysis, generate cultivation suggestions and continuously optimize environmental parameters.

[0040] Optionally, the cultivation suggestion generation includes:

[0041] Determine whether the currently optimized environmental parameters are suitable: Combine the results of growth trend analysis and environmental adaptability analysis to evaluate whether the current environmental parameters match the health status and growth requirements of Chinese herbal medicines. If the analysis results show that the environmental parameters are suitable, maintain the current settings; otherwise, mark them as unsuitable.

[0042] Adjust and optimize the unsuitable environmental parameters: Generate cultivation suggestions for the environmental parameters determined to be unsuitable, specifically including:

[0043] Unsuitable temperature: It is recommended to adjust it to the suitable range through heating or cooling equipment.

[0044] Unsuitable humidity: It is recommended to optimize the humidity through humidifying or dehumidifying equipment.

[0045] Insufficient or excessive light: It is recommended to optimize it by adjusting the light source intensity or light duration.

[0046] Lack of nutrients: It is recommended to apply corresponding fertilizers (supplement nitrogen, phosphorus, and potassium).

[0047] Advantages of the present invention:

[0048] First, in the present invention, by comprehensively monitoring environmental parameters in the cultivation environment, including temperature, humidity, light intensity, soil pH value, and nutrient content, and dynamically adjusting according to the real-time collected data, it can automatically adjust parameters such as temperature, humidity, and light intensity of the cultivation environment according to different environmental conditions, ensuring that the cultivation environment always remains in the most suitable state for the growth of Chinese herbal medicines, effectively optimizing the growth conditions of Chinese herbal medicines, improving the cultivation efficiency, reducing manual intervention, and realizing efficient and precise environmental management.

[0049] Second, in the present invention, through the health monitoring and warning module, it can monitor the health status of Chinese herbal medicines in real time, especially in terms of root development, leaf growth, and signs of pests and diseases. Through sensors and image recognition technology, it can timely detect plant health problems such as pests, diseases, and malnutrition, enabling potential risks in the cultivation process to be identified as early as possible and corresponding measures to be taken, thereby avoiding or reducing the outbreak of pests and diseases and optimizing the growth quality and yield of plants.

[0050] Third, in the present invention, through the intelligent scheduling and response module, it can automatically optimize the allocation of cultivation resources, including irrigation, fertilization, and pest control, ensuring the precise scheduling and efficient utilization of resources. At the same time, the data analysis module combines the results of growth trend analysis and environmental adaptability analysis to generate corresponding cultivation suggestions, continuously optimizing the cultivation environmental parameters, and can timely adjust the cultivation plan according to changes in the environment and growth conditions, realizing precise management, enhancing the sustainability and economic benefits of cultivation, and ensuring that the growth quality and yield of Chinese herbal medicines reach the optimal state. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only those of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0052] Figure 1 It is a schematic diagram of the system function modules of the embodiments of the present invention;

[0053] Figure 2 It is a schematic diagram of the health monitoring and early warning module of the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] The present invention will be described in detail below in conjunction with the drawings and specific embodiments. At the same time, it should be noted here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments. For some well-known technologies, those skilled in the art can also adopt other alternative methods for implementation; moreover, the drawings are only for more specifically describing the embodiments and are not intended to specifically limit the present invention.

[0055] It should be noted that in the specification, when referring to "an embodiment", "embodiment", "exemplary embodiment", "some embodiments", etc., it indicates that the described embodiment may include specific features, structures or characteristics, but not necessarily every embodiment includes the specific feature, structure or characteristic. In addition, when combining an embodiment to describe a specific feature, structure or characteristic, implementing such a feature, structure or characteristic in combination with other embodiments (whether explicitly described or not) should be within the knowledge of those skilled in the relevant art.

[0056] Generally, the terms can be understood at least in part from their use in the context. For example, at least in part depending on the context, the term "one or more" used herein can be used to describe any feature, structure or characteristic in a singular sense, or can be used to describe a combination of features, structures or characteristics in a plural sense. In addition, the term "based on" can be understood as not necessarily intended to convey a set of exclusive factors, but instead, at least in part depending on the context, allowing for the existence of other factors that may not be explicitly described.

[0057] As Figure 1 - Figure 2 shown, a Chinese herbal medicine cultivation system includes an environmental monitoring and regulation module, a health monitoring and early warning module, an intelligent scheduling and response module, and a data analysis module, wherein;

[0058] The environmental monitoring and regulation module monitors the environmental parameters in the cultivation environment in real time, including temperature, humidity, light intensity, soil pH value, and nutrient content, and optimizes the growth conditions of Chinese herbal medicines by adjusting the environmental parameters;

[0059] The health monitoring and early warning module monitors the health status of Chinese herbal medicines in real time, including root development, leaf growth conditions, and signs of pests and diseases, and analyzes pest and disease or nutritional problems based on the monitoring results of the health status;

[0060] The intelligent scheduling and response module optimizes the resources of the cultivation environment, including irrigation, fertilization, and pest control, based on the analysis results of pest and disease or nutritional problems;

[0061] The data analysis module analyzes the growth trend and environmental adaptability of Chinese herbal medicines and generates cultivation suggestions based on the optimized growth conditions of Chinese herbal medicines and the resources of the cultivation environment;

[0062] Through the above content, it is possible to monitor and optimize the cultivation environment in real time, timely discover plant health problems and automatically adjust resource allocation, thereby effectively improving cultivation efficiency, reducing manual intervention, improving the growth quality and yield of Chinese herbal medicines. Through data-driven prediction and optimization, precise management and continuous improvement can be achieved to meet the needs of different growth stages.

[0063] The environmental monitoring and regulation module includes:

[0064] Environmental parameter collection: Real-time monitoring of temperature, humidity, light intensity, soil pH value, and nutrient content in the cultivation environment through various sensors;

[0065] Temperature and humidity regulation: According to the real-time monitored temperature T real and humidity H real as well as the target temperature T set and target humidity H set , calculate the temperature and humidity deviation and automatically adjust the heating and humidification systems in the cultivation environment to achieve the optimal temperature and humidity growth conditions, expressed as:

[0066] ΔT = T set - T real ;

[0067] ΔH = H set - H real ;

[0068] where ΔT and ΔH are the adjustment amounts of temperature and humidity respectively;

[0069] Light intensity regulation: According to the real-time monitored light intensity L real and the preset target light intensity L set , calculate the light deviation and adjust the artificial light source in the cultivation area to achieve the predetermined light intensity, expressed as:

[0070] ΔL = L set - L real ;

[0071] Wherein, ΔL is the light deviation;

[0072] Soil pH and nutrient content regulation: According to the monitored soil pH real and nutrient content N real and the preset target soil pH set and target nutrient content N set , calculate the deviation of soil pH and nutrient content and automatically control the soil adjustment equipment (such as pH regulator or fertilization system) to adjust the soil pH and nutrients to the optimal range, expressed as:

[0073] ΔpH = pH set - pH real ;

[0074] ΔN = N set - N real ;

[0075] Wherein, ΔpH and ΔN are the deviations of soil pH and nutrient content respectively;

[0076] Through the above content, the environmental conditions can be precisely controlled, the growth environment of Chinese herbal medicines can be optimized, and through the automatic adjustment of various environmental parameters, dynamic adjustment can be made according to the real-time needs of plants, improving the accuracy and efficiency of cultivation management, avoiding human operation errors and resource waste, effectively improving the growth quality and yield of Chinese herbal medicines, while reducing energy consumption and management costs, having a high level of automation and sustainability, and further promoting the development of intelligent agriculture.

[0077] The health monitoring and early warning module includes:

[0078] Plant health monitoring: Through sensors and image recognition technology, the health status of Chinese herbal medicines is monitored in real time, including root development, leaf growth conditions and pest and disease signs;

[0079] Health status analysis: Based on the monitored health status of Chinese herbal medicines, predict the outbreak risk of pests and diseases. At the same time, analyze whether Chinese herbal medicines lack key nutrient elements (nitrogen, phosphorus, potassium), and predict whether there is malnutrition in Chinese herbal medicines;

[0080] Through the above, it is possible to accurately identify root development, leaf growth, and signs of pests and diseases, ensuring that plants are in the best growth state. Through health status analysis, not only can the risk of pest and disease outbreaks be predicted, but also the problem of plant malnutrition can be detected in a timely manner, providing scientific early warnings and optimization suggestions. This helps cultivators identify potential problems at an early stage, take timely measures, significantly improve the accuracy and efficiency of cultivation management, reduce losses, and enhance the quality and yield of Chinese herbal medicines.

[0081] Plant health monitoring includes:

[0082] Monitoring of root development: By using X-ray to scan the image data of roots, identify whether there are problems such as root rot or stunted growth;

[0083] Monitoring of leaf growth: Measure the greenness and chlorophyll content of leaves through a spectral sensor (NDVI), capture leaf image data through a camera, identify the growth state of leaves, including chlorosis and wilting problems, and monitor the leaf temperature through a leaf temperature sensor;

[0084] Monitoring of signs of pests and diseases: By using a camera to capture the image data of leaves and stems, monitor the signs of pests and diseases, including wormholes, spots, and withering and yellowing;

[0085] Through the above, a comprehensive monitoring of the Chinese herbal medicine cultivation process is achieved. It can accurately monitor the health status of roots, the growth state of leaves, and the early signs of pests and diseases, discover potential problems in a timely manner, avoid pests, diseases, and nutritional imbalances during the plant growth process, significantly improve cultivation efficiency, reduce resource waste, lower the risk of pests and diseases, improve the growth quality and yield of Chinese herbal medicines, ensure that plants are in the most suitable growth environment, thereby optimizing agricultural production management and enhancing economic benefits.

[0086] Health status analysis includes:

[0087] Analysis of signs of pests and diseases: Based on the monitored health status of Chinese herbal medicines, use a convolutional neural network (CNN) model to extract the signs and features of pests and diseases of roots, leaves, and stems, including damaged areas, morphological features, and texture features, and calculate the damage score to represent the degree of pests and diseases of Chinese herbal medicines;

[0088] Prediction of malnutrition: Collect the key nutrient elements of the soil through a soil sensor, including the contents of nitrogen, phosphorus, and potassium, and evaluate the degree of nutrient deficiency N deficiency , expressed as:

[0089]

[0090] where N deficiency is the degree of nutrient deficiency, N soil, , P soil, , Ksoil are the contents of ammonia, phosphorus, and potassium in the soil, respectively, and N required is the standard nutrient content required for Chinese herbal medicines. If N deficiency > 0, it indicates that there is a problem of malnutrition in Chinese herbal medicines;

[0091] Through the above content, potential pest and disease risks can be detected at an early stage, and control measures can be taken in a timely manner, thus effectively reducing losses. At the same time, through the health analysis of plant roots, leaves, and soil, the nutrient deficiency situation can be accurately evaluated, ensuring timely adjustment of fertilizer application, optimizing nutrient supply, improving the health of plant growth, making cultivation management more precise, avoiding interference from human factors, and enabling efficient utilization of resources and improvement of the quality of Chinese herbal medicines.

[0092] The analysis of pest and disease signs includes:

[0093] Feature extraction: Use a convolutional neural network (CNN) model to analyze the image data of the collected roots, leaves, and stems, and extract the features F of pest and disease signs out , including the damaged area, morphological features, and texture features, expressed as:

[0094] F out = ReLU(∑ i,j (I input [i, j]·K[i, j]) + b);

[0095] Among them, F out is the output feature of the convolutional layer, I input [i, j] is the pixel value of the input image, K[i, j] is the convolutional kernel (filter), b is the bias term, and ReLU is the activation function;

[0096] Damage score calculation: Based on the output F of the convolutional neural network (CNN) model out , calculate the damage score I damage , which reflects the degree of pest and disease, ranging from 0 to 1, where 0 represents completely healthy and 1 represents severe damage, expressed as:

[0097]

[0098] Among them, σ is the Sigmoid function, w n is the weight of the output feature, F out [n] is the extracted feature, b damage is the bias term, and N is the number of features;

[0099] Judgment of the degree of pest and disease: According to the damage score I damage , the degree of pest and disease of Chinese herbal medicines is divided into multiple levels. When 0 ≤ I damageWhen I < 0.2, it indicates a healthy state. When 0.2 ≤ I damage < 0.5, it indicates a minor injury. When 0.5 ≤ I damage < 0.8, it indicates a moderate injury. When 0.8 ≤ I damage ≤ 1, it indicates a severe injury;

[0100] Through the above content, the damage area, morphological characteristics, and texture characteristics of plant diseases and pests can be accurately identified, solving the problems of time-consuming and laborious manual inspection and easy omission of inspection. By automatically calculating the damage score through the CNN model, the assessment of the degree of diseases and pests is made more objective, accurate, and real-time, thus providing a reliable basis for subsequent precise regulation and resource optimization, significantly improving the early warning and control efficiency of diseases and pests in Chinese herbal medicine cultivation, reducing plant losses, and enhancing the overall efficiency of agricultural production.

[0101] The intelligent scheduling and response module includes:

[0102] Scheduling resource judgment: According to the calculated degree of nutrient deficiency N deficiency , combined with the result of the judgment of the degree of diseases and pests, determine whether resource scheduling is required;

[0103] Resource optimization decision-making: Use an optimization algorithm to optimize the resource allocation in the cultivation environment, including irrigation, fertilization, and pest control, expressed as:

[0104] R opt = α·(I damage ·w irrigation ) + β·(N deficiency ·w fertilizer ) + γ·(P pest ·w pest_control );

[0105] Among them, R opt represents the optimized resource scheduling plan, I damage is the damage score of diseases and pests, indicating the degree of diseases and pests, N deficiency is the degree of nutrient deficiency, indicating the nutrient problem of the plant, P pest is the probability of the need for pest control, w irrigation , w fertilizer , w pest_control are the weight coefficients of irrigation, fertilization, and pest control respectively, and α, β, γ are the coefficients for adjusting each resource scheduling decision;

[0106] Through the above content, the resource utilization efficiency is improved, over-irrigation, over-fertilization, or over-pest control is avoided, thus reducing resource waste and environmental burden. At the same time, it can respond in real-time to changes in the growth status of plants, dynamically adjust the cultivation conditions, ensure that Chinese herbal medicine grows in the best environment, and improve the yield and quality.

[0107] The scheduling resource judgment includes:

[0108] No need to schedule resources: When I damage <0.2 and N deficiency <0.2, the degree of pest and disease is low and the nutrition is sufficient, so there is no need to schedule resources. When 0.2 ≤ I damage <0.5 and N deficiency <0.2, there are slight pest and disease damages, but the nutrition is sufficient, so there is no need to schedule resources. When I damage <0.2 and 0.2 ≤ N deficiency <0.5, there are no problems with pests and diseases, but the nutrition is slightly insufficient, so there is no need to schedule resources;

[0109] Optimize resource scheduling: When I damage ≥0.5, the pest and disease damages are serious and resource scheduling needs to be optimized. When 0.2 ≤ I damage <0.5 and N deficiency ≥0.5, there are slight pest and disease damages, and at the same time the nutrition is severely lacking, so resource scheduling needs to be optimized. When N deficiency ≥0.5 and I damage <0.2, the nutrition is severely lacking and the plant growth is restricted, so resource scheduling needs to be optimized;

[0110] Through the above content, it is not only possible to respond to the changing needs of plants in real time, but also to avoid excessive waste of resources and unnecessary interventions, ensuring that operations such as pest control and fertilization are only carried out when necessary, improving the utilization efficiency of resources. At the same time, precise resource scheduling can optimize the plant growth environment, improve the health and growth quality of Chinese herbal medicines, and ultimately increase yields and economic benefits.

[0111] The data analysis module includes:

[0112] Growth trend analysis: Based on the optimized environmental parameters, use a linear regression model to predict the future growth trend of Chinese herbal medicines, expressed as:

[0113] y growth (t) = β 0 +β 1 ·X environment (t)+∈;

[0114] Among them, y growth (t) is the growth amount of Chinese herbal medicines at time t, X environment (t) is the optimized cultivation environment parameter, β 0 ,β 1 are regression coefficients, and ∈ is the error term;

[0115] Environmental adaptability analysis: By comparing the health status of Chinese herbal medicines with changes in environmental parameters, the support vector machine (SVM) model is used to analyze the environmental adaptability of Chinese herbal medicines and determine whether the cultivation environment is most suitable for the growth of current Chinese herbal medicines, expressed as:

[0116] f(x) = w T x + b;

[0117] Among them, f(x) is the decision function, w is the weight vector, b is the bias term, and x is the input vector, including the health status of Chinese herbal medicines and environmental parameters;

[0118] y = sign(w T x + b);

[0119] Among them, y is the output result. If y = +1, it means the cultivation environment is suitable; if y = -1, it means the cultivation environment is not suitable;

[0120] Cultivation suggestion generation: Based on the results of growth trend analysis and environmental adaptability analysis, cultivation suggestions are generated to continuously optimize environmental parameters;

[0121] Through the above content, the growth trend and environmental adaptability of Chinese herbal medicines can be accurately analyzed and predicted. This not only helps to identify potential cultivation problems in advance but also adjusts and optimizes cultivation conditions based on real-time environment, ensuring that plants grow in the best state, improving the intelligence and automation level of the cultivation process, reducing manual intervention, increasing resource utilization efficiency, and helping to optimize the growth performance of Chinese herbal medicines under different environmental conditions.

[0122] Cultivation suggestion generation includes:

[0123] Judge whether the current optimized environmental parameters are suitable: Combining the results of growth trend analysis and environmental adaptability analysis, evaluate whether the current environmental parameters match the health status and growth requirements of Chinese herbal medicines. If the analysis result shows that the environmental parameters are suitable, keep the current settings; otherwise, mark them as not suitable;

[0124] Adjust and optimize unsuitable environmental parameters: For the environmental parameters determined to be unsuitable, generate cultivation suggestions, specifically including:

[0125] Temperature is not suitable: It is recommended to adjust to the suitable range through heating or cooling equipment;

[0126] Humidity is not suitable: It is recommended to optimize the humidity through humidification or dehumidification equipment;

[0127] Insufficient or excessive light: It is recommended to optimize by adjusting the light source intensity or light duration;

[0128] Lack of nutrients: It is recommended to apply corresponding fertilizers (supplement nitrogen, phosphorus, and potassium);

[0129] Through the above, it is possible to dynamically respond to the growth requirements of Chinese herbal medicines, avoiding over-intervention or resource waste, while ensuring that the cultivation environment is always in the best state. Through clear judgment and targeted adjustment, problems can be quickly identified and optimization solutions can be proposed, making the growth of Chinese herbal medicines healthier, with higher yields and better quality. This closed-loop dynamic optimization process reduces the complexity of manual operations and enhances the intelligence and reliability of the cultivation system.

[0130] This invention covers any alternatives, modifications, equivalent methods, and solutions made within the essence and scope of this invention. To enable the public to have a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments of this invention. However, those skilled in the art can fully understand this invention even without the description of these details. Additionally, to avoid unnecessary confusion about the essence of this invention, well-known methods, processes, procedures, components, and circuits, etc. are not described in detail.

[0131] The above are only the preferred embodiments of this invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of this invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as within the protection scope of this invention.

Claims

1. A Chinese herbal medicine cultivation system, characterized in that: It includes environment monitoring and control module, health monitoring and early warning module, intelligent scheduling and response module and data analysis module, among which; The environmental monitoring and control module monitors the environmental parameters in the cultivation environment in real time, including temperature, humidity, light intensity, soil pH and nutrient content, and optimizes the growth conditions of Chinese herbal medicines by adjusting the environmental parameters; The health monitoring and early warning module monitors the health status of Chinese herbal medicines in real time, including root development, leaf growth and signs of pests and diseases, and analyzes pests and diseases or nutritional problems based on the monitoring results of the health status; The intelligent scheduling and response module optimizes the resources of the cultivation environment, including irrigation, fertilization, and pest and disease control, based on the analysis results of pests and diseases or nutritional problems; The data analysis module analyzes the growth trend and environmental adaptability of the Chinese herbal medicine based on the optimized growth conditions of the Chinese herbal medicine and the resources of the cultivation environment, and generates cultivation suggestions.

2. A Chinese herbal medicine cultivation system according to claim 1, characterized in that: The environmental monitoring and control module includes: Environmental parameter collection: Real-time monitoring of temperature, humidity, light intensity, soil pH and nutrient content in the cultivation environment through a variety of sensors; Temperature and humidity adjustment: According to the real-time monitored temperature T real and humidity H real and the target temperature T set and target humidity H set , calculate temperature and humidity deviations and automatically adjust the heating and humidification systems in the cultivation environment; Light intensity adjustment: According to the real-time monitored light intensity l real and preset target light intensity L set , calculate the light deviation and adjust the artificial light source in the cultivation area; Soil pH and nutrient content adjustment: According to the monitored soil pH real and nutrient content N real The preset target soil pH set and target nutrient content N set , calculate the deviation of soil pH and nutrient content and automatically control the soil conditioning equipment to adjust the soil pH and nutrients to the optimal range.

3. A Chinese herbal medicine cultivation system according to claim 1, characterized in that: The health monitoring and early warning module includes: Plant health monitoring: Using sensors and image recognition technology, real-time monitoring of the health of Chinese herbal medicines, including root development, leaf growth, and signs of pests and diseases; Health status analysis: Based on the monitored health status of Chinese herbal medicines, the risk of disease and insect pest outbreaks is predicted. At the same time, it is analyzed whether the Chinese herbal medicines lack key nutrients and whether there are malnutrition problems in the Chinese herbal medicines.

4. A Chinese herbal medicine cultivation system according to claim 3, characterized in that: The plant health monitoring includes: Root development monitoring: Use X-ray scanning to obtain root image data to identify whether the roots are rotten or poorly developed; Leaf growth monitoring: Use spectral sensors to measure the greenness and chlorophyll content of leaves, use cameras to capture leaf image data, identify leaf growth status, including yellowing and wilting, and use leaf temperature sensors to monitor leaf temperature; Monitoring of signs of pests and diseases: The camera captures image data of leaves and stems to monitor signs of pests and diseases, including insect holes, spots, and yellowing.

5. A Chinese herbal medicine cultivation system according to claim 4, characterized in that: The health status analysis includes: Pest and disease sign analysis: Based on the monitored health status of Chinese herbal medicines, a convolutional neural network model is used to extract the pest and disease sign characteristics of the roots, leaves and stems, including the damaged area, morphological characteristics and texture characteristics, and the damage score is calculated to indicate the degree of pest and disease of the Chinese herbal medicines; Malnutrition prediction: The key nutrient elements of the soil, including nitrogen, phosphorus, and potassium, are collected by soil sensors and combined with the standard nutrient content required by Chinese herbal medicines to assess the degree of nutrient deficiency. deficiency .

6. A Chinese herbal medicine cultivation system according to claim 5, characterized in that: The pest and disease evidence analysis includes: Feature extraction: A convolutional neural network model is used to analyze the collected image data of roots, leaves, and stems to extract the features of pests and diseases. out , including damage area, morphological characteristics, and texture characteristics; Damage score calculation: based on the output F of the convolutional neural network model out , calculate the injury score I damage , reflects the degree of pests and diseases, ranging from 0 to 1, where 0 indicates complete health and 1 indicates severe damage; Determination of pest and disease severity: Based on the damage score I damage , the degree of pests and diseases of Chinese herbal medicines is divided into multiple levels, when 0≤I damage <0.2, it indicates a healthy state. When 0.2≤I damage <0.5, it indicates slight damage. When 0.5≤I damage <0.8, indicating moderate damage, when 0.8≤I damage When ≤1, it indicates severe injury.

7. A Chinese herbal medicine cultivation system according to claim 6, characterized in that: The intelligent scheduling and response module includes: Scheduling resource judgment: Based on the calculated nutrient deficiency level N deficiency , combined with the results of the pest and disease severity assessment, determine whether resources need to be dispatched; Resource optimization decision-making: Use optimization algorithms to optimize resource allocation in the cultivation environment, including irrigation, fertilization, and pest and disease control.

8. A Chinese herbal medicine cultivation system according to claim 7, characterized in that: The scheduling resource determination includes: No need to schedule resources: When I damage <0.2 and N deficiency <0.2, the degree of pests and diseases is low and the nutrition is sufficient, so there is no need to dispatch resources. damage <0.5 and N deficiency <0.2, there is slight damage from pests and diseases, but the nutrition is sufficient and no resources need to be dispatched. damage <0.2 and 0.2≤N deficiency When <0.5, there is no problem with pests and diseases, but there is a slight nutritional deficiency and no resources need to be allocated; Optimizing resource scheduling: When I damage ≥0.5, the damage caused by pests and diseases is serious, and resource scheduling needs to be optimized. damage <0.5 and N deficiency When N is ≥0.5, there is slight damage from pests and diseases, and serious nutrient deficiency, and resource scheduling needs to be optimized. deficiency ≥0.5 and I damage When <0.2, there is a serious lack of nutrients, plant growth is restricted, and resource scheduling needs to be optimized.

9. A Chinese herbal medicine cultivation system according to claim 1, characterized in that: The data analysis module includes: Growth trend analysis: Based on the optimized environmental parameters, a linear regression model is used to predict the future growth trend of Chinese herbal medicines; Environmental adaptability analysis: By comparing the health status of Chinese herbal medicines with changes in environmental parameters, the support vector machine model is used to analyze the environmental adaptability of Chinese herbal medicines to determine whether the cultivation environment is most suitable for the growth of current Chinese herbal medicines; Cultivation suggestion generation: Generate cultivation suggestions based on the results of growth trend analysis and environmental adaptability analysis to continuously optimize environmental parameters.

10. A Chinese herbal medicine cultivation system according to claim 9, characterized in that: The cultivation suggestion generation includes: Determine whether the currently optimized environmental parameters are suitable: Combine the results of growth trend analysis and environmental adaptability analysis to evaluate whether the current environmental parameters match the health status and growth requirements of Chinese herbal medicines. If the analysis results show that the environmental parameters are suitable, keep the current settings; otherwise, mark them as unsuitable. Adjust and optimize unsuitable environmental parameters: Generate cultivation suggestions for unsuitable environmental parameters, including: Unsuitable temperature: It is recommended to adjust to a suitable range through heating or cooling equipment; Unsuitable humidity: It is recommended to optimize humidity through humidification or dehumidification equipment; Insufficient or excessive light: It is recommended to optimize by adjusting the light intensity or lighting duration; Nutrient deficiency: It is recommended to apply appropriate fertilizers.

Images