Intelligent agricultural greenhouse irrigation control system

Abstract

The invention relates to the technical field of agricultural automation, and discloses an intelligent agricultural greenhouse irrigation control system, which comprises system planning and design, prototype verification and simulation test, hardware installation and configuration, software programming and debugging, and system online and optimization. According to the intelligent agricultural greenhouse irrigation control system, by integrating edge computing integration, AI-driven adaptive learning and application of the block chain technology, the burden of the cloud server is relieved, the local decision process is accelerated, the real-time performance and reliability of the system are enhanced, and especially under the condition that network connection is unstable, the intelligent agricultural greenhouse irrigation control system has the advantages that the intelligent agricultural greenhouse irrigation control system is convenient to use. The system can automatically adjust the irrigation strategy according to historical data, improves the resource utilization efficiency, reduces the demands of manual intervention, achieves more intelligent management, enhances the transparency and safety of data, increases the credibility of the system, meets the requirements of the market for the quality guarantee of agricultural products, and is worthy of popularization and application. Therefore, the effect of flexibly adjusting irrigation according to growth conditions and factors of crops can be achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of agricultural automation, in particular to a smart agricultural greenhouse irrigation control system. BACKGROUND

[0002] Smart agricultural greenhouse irrigation is an important component of modern agricultural technology, which combines sensor technology, automation control, Internet of Things, big data analysis and cloud computing, and other modern information technologies to realize intelligent management and optimization of the irrigation system in the agricultural greenhouse. This system can accurately provide water according to the needs of crops, thereby improving water resource utilization, ensuring healthy growth of crops, and reducing labor costs.

[0003] Traditional agricultural irrigation methods rely heavily on manual experience, lack of scientific nature and precision, resulting in waste of water resources and poor crop growth, and cannot automatically adjust flexibly according to soil moisture, weather forecast, plant water demand and other factors, reducing water and fertilizer utilization and increasing labor costs. SUMMARY

[0004] (I) Technical problems solved

[0005] In view of the deficiencies in the prior art, the present application provides a smart agricultural greenhouse irrigation control system, which has the advantages of being able to flexibly adjust irrigation according to the growth conditions and factors of crops, and solves the problems mentioned in the background art.

[0006] (II) Technical solutions

[0007] To achieve the above purpose, the present application provides the following technical solutions: a smart agricultural greenhouse irrigation control system, including system planning and design, prototype verification and simulation test, hardware installation and configuration, software programming and debugging, system online and optimization, maintenance and support, and life cycle evaluation and green upgrade, the system planning and design includes demand analysis and system architecture design, the hardware installation and configuration includes installing sensors, connecting control center and executing mechanism debugging, the software programming and debugging includes data processing algorithm writing, user interface development and system integration and testing, the system online and optimization includes initial setting, real-time monitoring and adjustment and data accumulation and learning, the maintenance and support includes regular inspection, fault diagnosis and repair and technical training and service.

[0008] Preferably, the demand analysis clarifies the core objectives of the system, such as increasing crop yields, saving water resources, and reducing labor costs, and conducts a detailed investigation of the specific location, area, types of crops planted, and growth cycles of the greenhouses to understand the operating habits, technical level, and expectations of farmers or managers for the system. The system architecture design includes functional module division and technology selection, and the system planning and design incorporates edge computing integration, AI-driven adaptive learning, and blockchain technology applications.

[0009] Preferably, the sensor is installed according to the requirements of different types of sensors, and the best installation position is selected to ensure the accuracy of data collection. The sensor is firmly fixed in the predetermined position using an appropriate bracket or clamp to prevent displacement due to wind or other external forces. The data cable and power cable of the sensor are connected to the corresponding interface according to the instructions, and attention is paid to waterproofing, especially for the outdoor part. The connection control center is installed and configured with a central controller to ensure that it can normally receive data from the sensor and issue control instructions. A wireless or wired network is set up according to the selected communication protocol to ensure unimpeded data transmission between the controller and other devices. The communication status of each node is checked to ensure that all sensors can successfully upload data to the controller and that the controller can correctly parse the data. The actuator debugging is based on irrigation needs. Actuators such as water pumps and solenoid valves are installed in appropriate locations and preliminary tests are carried out to ensure that they can operate correctly according to the preset instructions. The control port of the actuator is connected to the controller, and the correct wiring diagram is followed to ensure accurate signal transmission. The function of each actuator is tested one by one to simulate different irrigation scenarios to confirm that the system responds quickly and as expected.

[0010] Preferably, the data processing algorithm is coded to read data from different sensors and perform preliminary processing, such as filtering, calibration, unit conversion, etc. Based on the collected data, an irrigation decision algorithm is designed to predict crop water requirements and generate irrigation plans, and implement an automatic response mechanism under abnormal conditions, such as triggering an alarm when soil moisture is lower than a set value and notifying the administrator. The user interface development includes mobile application development, web interface development and user experience optimization. The system integration and testing includes modular programming, unit testing, integration testing, stress testing and security testing. The software programming and debugging incorporate AI-driven adaptive learning, blockchain technology applications, remote diagnosis and OTA updates.

[0011] Preferably, the initial setting sets the basic parameters of the system according to the results of the previous demand analysis, creates administrator accounts and other user roles, assigns corresponding permissions, ensures that users at different levels can only access and operate allowed functions, enables firewall, encrypted communication and other security mechanisms to protect the system from network attacks, the real-time monitoring and adjustment includes data collection and display, dynamic adjustment strategy and agenda processing mechanism, the data accumulation and learning includes historical data analysis, machine learning optimization and adaptive learning.

[0012] Preferably, the periodic inspection includes hardware device inspection, sensor calibration, cleaning and maintenance, and power system inspection, the fault diagnosis and repair includes recording common faults and their solutions to form a knowledge base to facilitate technicians to quickly locate problems and take corresponding measures, using SSH server, VNC Viewer and other remote access tools to allow the technical support team to perform preliminary troubleshooting without being present on site, developing detailed emergency response procedures to quickly activate backup solutions when serious failures occur to minimize losses, preparing necessary spare parts inventory such as commonly used sensors and control modules to replace immediately when problems occur, the technical training and service push the latest firmware and application program versions through over-the-air download to ensure that the system is always up-to-date, while fixing known vulnerabilities, adding new features or improving existing features based on user feedback and technology trends to improve the user experience of the system, and conducting comprehensive compatibility testing before releasing new updates to ensure that the normal operation of the system is not affected.

[0013] Preferably, the prototype verification and simulation test uses simulation software or builds a small-scale prototype to simulate system operation in a virtual environment to evaluate sensor response speed, data transmission efficiency and the effectiveness of control logic.

[0014] Preferably, the life cycle assessment and green upgrade conducts a comprehensive life cycle assessment of the existing system to identify which components can be replaced by more environmentally friendly options through upgrading, such as replacing with a new generation of sensors made of recyclable materials or replacing with a more energy-efficient water pump motor.

[0015] Compared with the prior art, the present application provides a smart agricultural greenhouse irrigation control system, which has the following advantages:

[0016] This smart agricultural greenhouse irrigation control system, by integrating edge computing integration, AI-driven adaptive learning and the application of blockchain technology, reduces the burden on cloud servers, speeds up the local decision-making process, and enhances the real-time and reliability of the system. Especially in the case of unstable network connection, it enables the system to automatically adjust irrigation strategies based on historical data, improves resource utilization efficiency, reduces the need for manual intervention, realizes more intelligent management, enhances data transparency and security, increases the credibility of the system, and meets the market requirements for agricultural product quality assurance, so as to achieve the purpose of flexibly adjusting irrigation according to crop growth conditions and factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the overall framework structure of the present invention. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0019] See also Figure 1 A smart agricultural greenhouse irrigation control system, including system planning and design, prototype verification and simulation testing, hardware installation and configuration, software programming and debugging, system launch and optimization, maintenance and support, and life cycle assessment and green upgrade. System planning and design include demand analysis and system architecture design. Hardware installation and configuration include sensor installation, control center connection and actuator debugging. Software programming and debugging include data processing algorithm writing, user interface development and system integration and testing. System launch and optimization include initial settings, real-time monitoring and adjustment, and data accumulation and learning. Maintenance and support include regular inspections, fault diagnosis and repair, and technical training and services.

[0020] The demand analysis clarifies the core objectives of the system, such as increasing crop yields, saving water resources, and reducing labor costs. A detailed investigation is conducted on the specific location, area, types of crops planted, and their growth cycles of the greenhouses to understand the operating habits, technical level, and expectations of farmers or managers for the system. The system architecture design includes functional module division and technology selection. The system planning and design incorporates edge computing integration, AI-driven adaptive learning, and blockchain technology applications.

[0021] By the above technical solution, the demand analysis ensures that the system design meets the actual needs, avoiding unnecessary function development, thereby saving resources, providing a clear direction and goal for subsequent design and implementation, improving the success rate of the project, reducing the risk of later changes, the system architecture design ensures the stability and scalability of the system, facilitating future upgrades and technical improvements, laying the technical foundation for the system, guiding the selection and integration of specific components, and improving the performance of the system and user experience. The edge computing is integrated into the local controller to add edge computing capabilities, allowing some data analysis and processing to be completed near the data source, reducing latency and saving bandwidth, reducing the burden on cloud servers, and speeding up the local decision-making process. The AI-driven adaptive learning uses machine learning algorithms to learn from past irrigation records to predict the changing trend of crop demand and dynamically optimize irrigation plans, allowing the system to automatically adjust irrigation strategies based on historical data, improving resource utilization efficiency and reducing the need for manual intervention, achieving more intelligent management. The application of blockchain technology uses blockchain technology to record all operation logs and transaction information, ensuring that data cannot be tampered with and is traceable, suitable for organic certification or food traceability, enhancing data transparency and security, increasing the credibility of the system, and meeting market requirements for quality assurance of agricultural products.

[0022] Installing sensors requires selecting the best installation location based on the requirements of different types of sensors to ensure the accuracy of data collection, using appropriate brackets or clamps to securely fix the sensors in the predetermined position, preventing displacement due to wind or other external forces, connecting the data line and power line of the sensor to the corresponding interface according to the instructions, paying attention to waterproof treatment, especially for outdoor parts, installing and configuring the central controller to ensure it can normally receive data from the sensor and issue control instructions, setting up wireless or wired networks according to the selected communication protocol to ensure smooth data transmission between the controller and other devices, checking the communication status of each node to ensure that all sensors can successfully upload data to the controller and the controller can correctly parse these data, and executing mechanism debugging according to irrigation requirements, installing water pumps, solenoid valves, and other executing mechanisms at appropriate locations and performing preliminary testing to ensure they can act correctly according to the preset instructions, connecting the control port of the executing mechanism to the controller, following the correct wiring diagram to ensure accurate signal transmission, and testing the function of each executing mechanism one by one, simulating different irrigation scenarios to confirm that the system responds quickly and meets expectations.

[0023] Through the above technical solution, the installation of sensors provides accurate environmental data, supports scientific decision-making, realizes real-time monitoring of the internal environment of the greenhouse, enhances the intelligent level of the system, improves management efficiency, and connects the control center as the "brain" of the system, responsible for receiving data and issuing instructions, simplifying system operation, improving response speed, enhancing system coordination and automation level, and implementing irrigation plan execution to ensure normal operation of the system, reduce failure rate, improve irrigation accuracy, and reduce water waste.

[0024] Data processing algorithm writing writes code to read data from different sensors and performs preliminary processing such as filtering, calibration, unit conversion, etc. Based on the collected data, design irrigation decision-making algorithms to predict crop water demand and generate irrigation plans, implement automatic response mechanisms in abnormal situations such as triggering alarms when soil humidity is below a set value and notifying administrators. User interface development includes mobile application development, web interface development, and user experience optimization. System integration and testing include modular programming, unit testing, integration testing, stress testing, and security testing. Software programming and debugging incorporate AI-driven adaptive learning, blockchain technology application, and remote diagnosis and OTA updates.

[0025] Through the above technical solution, the system can dynamically adjust irrigation strategies according to actual conditions, optimize irrigation schemes, improve resource utilization, promote crop healthy growth, increase yield, and create user-friendly interfaces that allow farmers to remotely monitor and manage irrigation systems, providing intuitive human-computer interaction, improving user operation experience, reducing learning costs, and facilitating daily management and maintenance. System integration and testing integrate individual subsystems and conduct comprehensive functional testing to verify the effectiveness of the design scheme, ensuring overall system stability, reducing potential problems, improving system reliability, enhancing user confidence, introducing machine learning algorithms to predict crop demand trends by learning from past irrigation records, dynamically optimizing irrigation plans, using blockchain technology to record all operation logs and transaction information, enhancing data transparency and security, suitable for organic certification or food traceability, supporting remote access to the system for troubleshooting, and allowing the latest firmware and application versions to be pushed through over-the-air upgrades.

[0026] Initial settings set the basic parameters of the system based on the results of the preliminary demand analysis, create administrator accounts and other user roles, assign appropriate permissions to ensure that users at different levels can only access and operate permitted functions, enable firewall, encrypted communication, and other security mechanisms to protect the system from network attacks, real-time monitoring and adjustment including data collection and display, dynamic adjustment strategies, and agenda processing mechanisms, data accumulation and learning including historical data analysis, machine learning optimization, and adaptive learning.

[0027] Through the above technical solution, the initial settings provide the necessary configuration for the first operation of the system, so that the system can be put into use immediately, reducing preparation time, accelerating the deployment of the project, and improving the initial use experience. Real-time monitoring and adjustment ensure that crops are always in the best growth environment, improving the adaptability and flexibility of the system, promoting the healthy growth of crops, and increasing yield and quality. Data accumulation and learning: With the long-term operation of the system, a large amount of historical data is accumulated and analyzed through machine learning algorithms, realizing the self-optimization and personalized service of the system, continuously optimizing irrigation plans, improving resource utilization efficiency, and promoting the refined management and sustainable development of agricultural production.

[0028] Regular inspections include hardware equipment inspections, sensor calibration, cleaning and maintenance, and power system inspections. Fault diagnosis and repair include recording common faults and their solutions to form a knowledge base, allowing technicians to quickly locate problems and take appropriate measures. Remote access tools such as SSH servers and VNC Viewers are used to allow the technical support team to conduct preliminary inspections without visiting the site. Detailed emergency response procedures are developed to enable rapid activation of backup plans in the event of serious faults to minimize losses. Necessary spare parts inventories are prepared, such as common sensors and control modules, so that they can be replaced immediately when problems arise. Technical training and services push the latest firmware and application versions via over-the-air downloads to ensure that the system is always up to date and to fix known vulnerabilities. Based on user feedback and technological development trends, new features are continuously added or existing features are improved to enhance the system's user experience. Before launching new updates, comprehensive compatibility testing is performed to ensure that they will not affect the normal operation of the system.

[0029] Through the above technical solutions, regular inspections and maintenance are carried out on all hardware equipment, and aging components are replaced to ensure the long-term stable operation of the system, prevent possible failures, maintain the efficient operation of the system, extend the service life of the equipment, reduce maintenance costs, and improve the reliability and safety of the system. Fault diagnosis and repair: when abnormal situations occur, the problem is located in time and effective measures are taken to solve it, ensuring the continuous operation of the system, shortening the fault recovery time, reducing economic losses, and enhancing user satisfaction and trust. Technical training and services provide users with necessary technical support and training to help them master how to use and maintain the system effectively, solve users' questions and problems, improve users' skills, promote the popularization and application of the system, enhance users' service experience, and establish good customer relationships.

[0030] Prototype verification and simulation testing use simulation software or build small-scale prototypes to simulate system operation in a virtual environment to evaluate sensor response speed, data transmission efficiency, and the effectiveness of control logic.

[0031] Through the above technical solutions, we can confirm whether the selected technology and architecture can meet the needs of actual application scenarios, test the system's performance in terms of response speed, data transmission efficiency, algorithm accuracy, etc., collect users' preliminary evaluations on interface friendliness, ease of operation, etc., and provide a basis for subsequent improvements. By discovering potential design defects and technical problems at an early stage, we can reduce the risk of rework after large-scale deployment, avoid expensive repair measures such as large-scale hardware replacement or rewiring due to design errors, provide opportunities for iterative optimization of design solutions, ensure that the final product better meets the expected needs, increase the possibility of project completion on time and with quality, enhance customer confidence, promote the application of new technologies such as edge computing and AI-driven decision-making, and promote technological progress in the industry.

[0032] Life Cycle Assessment and Green Upgrades A comprehensive life cycle assessment of the existing system identifies components that can be replaced through upgrades with greener options, such as new-generation sensors made from recyclable materials or replacement with more energy-efficient pump motors.

[0033] Through the above technical solutions, by optimizing energy utilization and material selection, the consumption of natural resources is reduced, carbon emissions and the release of other pollutants in the production process are reduced, which meets the current social requirements for environmental protection. The application of energy-saving equipment and renewable energy can significantly reduce operating costs, support the concept of circular economy, promote the effective management and reuse of waste, and ensure that products and services comply with increasingly stringent environmental regulations and standards.

[0034] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A smart agricultural greenhouse irrigation control system, including system planning and design, prototype verification and simulation testing, hardware installation and configuration, software programming and debugging, system launch and optimization, maintenance and support, and life cycle assessment and green upgrades, characterized by: The system planning and design includes demand analysis and system architecture design; the hardware installation and configuration includes sensor installation, control center connection and actuator debugging; the software programming and debugging includes data processing algorithm writing, user interface development and system integration and testing; the system launch and optimization includes initial setup, real-time monitoring and adjustment, and data accumulation and learning; the maintenance and support includes regular inspections, fault diagnosis and repair, and technical training and services.

2. The smart agricultural greenhouse irrigation control system according to claim 1, characterized in that: The demand analysis defines the core objectives of the system, such as increasing crop yields, saving water resources, and reducing labor costs. A detailed investigation is conducted on the specific location, area, types of crops planted, and growth cycles of the greenhouses to understand the operating habits, technical level, and expectations of farmers or managers for the system. The system architecture design includes functional module division and technology selection. The system planning and design incorporates edge computing integration, AI-driven adaptive learning, and blockchain technology applications.

3. The smart agricultural greenhouse irrigation control system according to claim 1, characterized in that: The sensor installation is based on the requirements of different types of sensors, and the best installation position is selected to ensure the accuracy of data collection. The sensor is firmly fixed in the predetermined position using an appropriate bracket or clamp to prevent displacement due to wind or other external forces. The data cable and power cable of the sensor are connected to the corresponding interface according to the instructions, and attention is paid to waterproofing, especially for the outdoor part. The connection control center is installed and configured with a central controller to ensure that it can normally receive data from the sensor and issue control instructions. A wireless or wired network is set up according to the selected communication protocol to ensure unimpeded data transmission between the controller and other devices. The communication status of each node is checked to ensure that all sensors can successfully upload data to the controller and that the controller can correctly parse the data. The actuator debugging is based on irrigation needs. Actuators such as water pumps and solenoid valves are installed in appropriate locations and preliminary tests are carried out to ensure that they can operate correctly according to the preset instructions. The control port of the actuator is connected to the controller, and the correct wiring diagram is followed to ensure accurate signal transmission. The function of each actuator is tested one by one to simulate different irrigation scenarios to confirm that the system responds quickly and as expected.

4. The smart agricultural greenhouse irrigation control system according to claim 1, characterized in that: The data processing algorithm is coded to read data from different sensors and perform preliminary processing, such as filtering, calibration, unit conversion, etc. Based on the collected data, an irrigation decision algorithm is designed to predict crop water requirements and generate irrigation plans, and implement automatic response mechanisms in abnormal situations. For example, when soil moisture is lower than the set value, an alarm is triggered and the administrator is notified. The user interface development includes mobile application development, web interface development and user experience optimization. The system integration and testing includes modular programming, unit testing, integration testing, stress testing and security testing. The software programming and debugging incorporate AI-driven adaptive learning, blockchain technology applications, remote diagnosis and OTA updates.

5. The smart agricultural greenhouse irrigation control system according to claim 1, characterized in that: The initial settings set the basic parameters of the system based on the results of the previous demand analysis, create administrator accounts and other user roles, and assign corresponding permissions to ensure that users at different levels can only access and operate permitted functions. Firewalls, encrypted communications and other security mechanisms are enabled to protect the system from network attacks. The real-time monitoring and adjustment include data collection and display, dynamic adjustment strategies and agenda processing mechanisms. The data accumulation and learning include historical data analysis, machine learning optimization and adaptive learning.

6. The smart agricultural greenhouse irrigation control system according to claim 1, characterized in that: The regular inspections include hardware equipment inspections, sensor calibration, cleaning and maintenance, and power system inspections. The fault diagnosis and repairs include recording common faults and their solutions to form a knowledge base, allowing technicians to quickly locate problems and take corresponding measures. Remote access tools such as SSH servers and VNC Viewers are used to allow the technical support team to conduct preliminary inspections without visiting the site. Detailed emergency response procedures are formulated to enable backup plans to be quickly activated in the event of a serious fault to minimize losses. Necessary spare parts inventories are prepared, such as common sensors and control modules, so that they can be replaced immediately when problems arise. The technical training and services push the latest firmware and application versions via over-the-air downloads to ensure that the system is always up to date, while fixing known vulnerabilities. Based on user feedback and technological development trends, new features are continuously added or existing features are improved to enhance the system's user experience. Before launching new updates, comprehensive compatibility testing is performed to ensure that they will not affect the normal operation of the system.

7. The smart agricultural greenhouse irrigation control system according to claim 1, characterized in that: The prototype verification and simulation test uses simulation software or builds a small-scale prototype to simulate system operation in a virtual environment to evaluate sensor response speed, data transmission efficiency, and effectiveness of control logic.

8. The smart agricultural greenhouse irrigation control system according to claim 1, characterized in that: The Life Cycle Assessment and Green Upgrades process conducts a comprehensive life cycle assessment of the existing system to identify components that can be replaced through upgrades with more environmentally friendly options, such as new generation sensors made from recyclable materials or replacement with more energy-efficient pump motors.

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