An automatic agricultural irrigation method and system based on the Internet of Things

Abstract

This invention discloses an automated agricultural irrigation method and system based on the Internet of Things (IoT), relating to the field of agricultural irrigation technology. The method includes: real-time monitoring of the agricultural irrigation environment and acquisition of environmental and crop data; processing and analyzing the environmental and crop data to generate an irrigation strategy; generating control commands based on the irrigation strategy and controlling irrigation equipment to perform agricultural irrigation; acquiring and analyzing historical irrigation data to generate an adaptive strategy; and adaptively adjusting the irrigation strategy to optimize it. This invention improves agricultural irrigation efficiency and yield while reducing resource waste by acquiring and analyzing environmental and crop data to generate irrigation strategies; it also ensures data reliability and stability through network transmission using a combination of ZigBee and LoRaWAN technologies; and it guarantees the power supply for irrigation by employing an energy conversion system to convert natural resources into electrical energy.

Description

Technical Field

[0001] This invention belongs to the field of agricultural irrigation technology, and in particular relates to an automated agricultural irrigation method and system based on the Internet of Things. Background Technology

[0002] Agricultural irrigation refers to the use of water resources in agricultural production, through artificial means to introduce water and fertilizer into farmland to meet the growth needs of crops. However, existing agricultural irrigation methods cannot precisely control water resources and nutrients such as fertilizers, and cannot take into account various environmental factors such as soil, sunlight, temperature, and humidity. As a result, existing agricultural irrigation methods suffer from a variety of problems, including low resource utilization, low crop yields, and low irrigation efficiency.

[0003] With the rapid development of the Internet of Things (IoT), agricultural irrigation integrating IoT technology has also achieved a significant leap forward. IoT technology can bring intelligent control to agricultural irrigation, improving its efficiency and economic benefits in many ways. However, agricultural irrigation equipped with IoT technology still faces many problems due to technological limitations. For example, incomplete monitoring and analysis of agricultural environmental data prevents more precise control of crop growth; imprecise control of water, fertilizer, and pesticide application leads to lower-than-expected crop yields and increased resource waste; the inability to effectively utilize natural resources such as solar and wind power to ensure power supply and increase crop yields; and data leakage / tampering in the IoT system challenges the security and stability of agricultural irrigation systems and affects irrigation efficiency. Summary of the Invention

[0004] The purpose of this invention is to provide an automated agricultural irrigation method and system based on the Internet of Things (IoT). By acquiring and analyzing environmental and crop data to generate irrigation strategies, it improves agricultural irrigation efficiency, reduces resource waste, and increases yield. It also uses a combination of ZigBee and LoRaWAN technologies for network transmission to ensure reliable data transmission and stability. Furthermore, it employs an energy conversion system to convert natural resources into electrical energy to ensure the power supply for irrigation.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] In a first aspect, embodiments of this application provide an automated agricultural irrigation method based on the Internet of Things, comprising the following steps:

[0007] Real-time monitoring of agricultural irrigation environment and acquisition of environmental and crop data;

[0008] The environmental data and crop data are processed and analyzed to generate irrigation strategies.

[0009] Based on the irrigation strategy, control commands are generated and used to control the irrigation equipment for agricultural irrigation.

[0010] Acquire and analyze historical irrigation data to generate adaptive strategies;

[0011] The irrigation strategy is adaptively adjusted according to the adaptive strategy to optimize the irrigation strategy.

[0012] The environmental data includes soil conditions, meteorological conditions, irrigation conditions, and equipment conditions;

[0013] The crop data includes growth conditions, growth factors, and growth status;

[0014] Generating the irrigation strategy includes the following steps:

[0015] A first relationship is established based on the soil conditions and the crop data;

[0016] A second relationship is established based on the meteorological conditions and the crop data;

[0017] Establish a third relation based on the first and second relations;

[0018] An irrigation strategy is generated based on the third relation.

[0019] The third relation is expressed as: W = W1 + W2;

[0020] Where W represents the total amount of irrigation water and fertilizer required for crop growth; W1 represents the first amount of irrigation water and fertilizer; and W2 represents the second amount of irrigation water and fertilizer.

[0021] Preferably, the soil conditions include the degree of salinization, water content, water holding capacity, and soil fertility; the meteorological conditions include temperature, humidity, light intensity, geographical data, and meteorological data; the irrigation conditions include water level, water quantity, water quality, and pests and diseases; and the equipment conditions include irrigation equipment, operating status, and degree of aging.

[0022] The geographic data includes the latitude, longitude, altitude, and topographic features of the agricultural irrigation environment; the meteorological data includes precipitation, sunshine hours, weather phenomena, seasonal changes, and wind direction and speed.

[0023] Preferably, in the crop data, the growth conditions represent the growth requirements necessary for crop growth, including water requirement, fertilizer requirement, light requirement, soil requirements, water quality requirements, planting time, and climate environment; the growth factors represent the nutrient elements necessary for crop growth, including nitrogen, phosphorus, potassium, iron, and zinc; and the growth status represents the growth state exhibited by the crop at different growth stages.

[0024] Preferably, real-time monitoring of the agricultural irrigation environment includes:

[0025] Multiple sensors, including environmental sensors and crop sensors, are deployed around the agricultural irrigation environment.

[0026] The first sensor network node is established using ZigBee technology;

[0027] Deploy LoRaWAN gateways in the periphery / center of agricultural irrigation environments;

[0028] A second sensor network node is established using LoRaWAN technology;

[0029] Establish a remote control terminal, including a cloud server / local control center;

[0030] Specifically, the first sensor network node establishes a network connection with the second sensor network node; the second sensor network node establishes a network connection with the remote control terminal.

[0031] The first sensor network node is used to monitor and collect data;

[0032] The second sensor network node is used to receive data sent by the first sensor network node and transmit the data to the remote control terminal via the LoRaWAN protocol;

[0033] The remote control terminal is used to receive and process data from the second sensor network node, and to analyze and store the data;

[0034] The environmental sensors include a salinity sensor, a moisture content sensor, a water holding capacity sensor, a soil fertility sensor, a temperature sensor, a humidity sensor, a light sensor, a water level sensor, a water quantity sensor, a water quality sensor, and a rain gauge.

[0035] The crop sensors include nutrient element sensors and growth status sensors.

[0036] Preferably, a multi-protocol gateway processor is used as an intermediate node between the first sensor network node and the second sensor network node, which includes a protocol conversion layer, a protocol support layer and a data processing layer;

[0037] The protocol conversion layer is used to convert the protocols used by ZigBee and LoRaWAN into a unified communication format;

[0038] The protocol support layer has the capability to support both the ZigBee and LoRaWAN protocols.

[0039] The data processing layer is used for receiving and forwarding data;

[0040] The protocol support layer includes a data transmission protocol frame format and a node authentication and encrypted transmission mechanism.

[0041] The data transmission protocol frame format is used to uniformly address all nodes and set the destination address to a unified address. Its communication frame format is as follows: Frame header: 2 bytes; ACK confirmation bit: 1 byte; Source address: 8 bytes; Destination address: 2 bytes; Data type: 1 byte; Data: 2 bytes; CRC check: 1 byte;

[0042] The node authentication and encrypted transmission mechanism is used to identify the identity of network nodes and establish a secure channel using a two-way non-repudiation digital signature mechanism; it is also used to encrypt data using symmetric encryption technology based on identity authentication and to store the key using a key pre-storage mechanism.

[0043] The key pre-store mechanism is specifically as follows:

[0044] An initial key is pre-stored in the node;

[0045] Store backups of the initial keys for all nodes in the network's base stations;

[0046] When the network encrypts data, nodes and base stations use their respective stored keys to encrypt and decrypt.

[0047] In the encryption and decryption process, random numbers are used as random step sizes to control the step size of data displacement during encryption.

[0048] Preferably, an energy conversion system and a power supply system are used to provide electrical support for equipment in agricultural irrigation, including the following steps:

[0049] Solar energy is captured and converted into first electrical energy through the energy conversion system;

[0050] The system acquires thermal energy and divides it into first thermal energy and second thermal energy, stores the first thermal energy, and converts the second thermal energy into second electrical energy through the energy conversion system.

[0051] Wind energy is harvested and converted into electrical energy through the energy conversion system.

[0052] Store the first electrical energy, the second electrical energy, and the third electrical energy;

[0053] The stability of the power supply system is assessed. If the power supply is stable, the first electrical energy is used as a supplementary energy source for the power supply system. If the power supply is unstable, the second electrical energy and / or the third electrical energy are used as supplementary energy sources for the power supply system.

[0054] The energy conversion system is constructed based on the meteorological conditions and includes a solar energy subsystem, a thermal energy subsystem, and a wind energy subsystem.

[0055] The solar energy subsystem is linked to sunlight, sunshine hours, and geographic data to convert solar energy into electrical energy.

[0056] The thermal energy subsystem is linked to temperature, light, and geographic data to store thermal energy and convert it into electrical energy.

[0057] The wind energy subsystem is linked with wind direction, wind speed, and geographical data to convert wind energy into electrical energy.

[0058] Among them, the temperature difference of the current agricultural irrigation environment is determined based on meteorological data. If the temperature difference is greater than the set temperature difference threshold, the first heat energy is released to provide heat energy for the agricultural irrigation environment.

[0059] The temperature difference threshold is set based on historical temperature difference data and crop growth conditions.

[0060] Preferably, the stability of the power supply system is assessed, specifically including:

[0061] The voltage fluctuations at each node in the power supply system are judged. If the voltage fluctuations exceed the set voltage range, the power supply system is judged to be unstable.

[0062] The frequency change of the power supply system is judged. If the frequency change exceeds the set frequency range, the power supply system is judged to be unstable.

[0063] The power balance among the various loads in the power supply system is judged. If an overload or underload occurs, the power supply system is judged to be unstable.

[0064] Conversely, the power supply system is considered stable.

[0065] Preferably, the first relation is expressed as:

[0066] W1 = P * h(H - (H0 + H1 + H2));

[0067] Where W1 represents the first irrigation water and fertilizer amount; P represents the growth status of crops; h() represents the mapping function between soil conditions and crop growth conditions; H represents the degree of soil salinization; H0 represents soil moisture content; H1 represents soil water holding capacity; and H2 represents soil fertility.

[0068] Preferably, the second relation is expressed as:

[0069] W2=P*f((F+F')-(F0+F1+F2));

[0070] Where W2 represents the second irrigation water and fertilizer amount; P represents the crop growth status; f() represents the mapping function between meteorological conditions and crop growth conditions; F represents meteorological data; F' represents geographical data; F0 represents temperature; F1 represents humidity; and F2 represents light intensity.

[0071] Secondly, embodiments of this application provide an automated agricultural irrigation system based on the Internet of Things, including a sensor module, a data communication module, a central control module, an adaptive optimization module, and an energy conversion module;

[0072] The sensor module is used to deploy several sensors and monitor the agricultural irrigation environment in real time to obtain environmental data and crop data.

[0073] The data communication module is used to establish a data transmission channel and encrypt the network connection;

[0074] The central control module is used to process and analyze the environmental data and the crop data and generate irrigation strategies; it also generates control commands based on the irrigation strategies and uses the control commands to control the irrigation equipment for agricultural irrigation.

[0075] The adaptive optimization module is used to acquire and analyze historical irrigation data to generate an adaptive strategy, and to make adaptive adjustments based on the adaptive strategy to optimize the irrigation strategy.

[0076] The energy conversion module is used to convert solar, wind and thermal energy into electrical energy and provide power support for equipment in agricultural irrigation;

[0077] The environmental data includes soil conditions, meteorological conditions, irrigation conditions, and equipment conditions;

[0078] The crop data includes growth conditions, growth factors, and growth status;

[0079] Generating the irrigation strategy includes the following steps:

[0080] A first relationship is established based on the soil conditions and the crop data;

[0081] A second relationship is established based on the meteorological conditions and the crop data;

[0082] Establish a third relation based on the first and second relations;

[0083] An irrigation strategy is generated based on the third relation.

[0084] The beneficial effects of this invention are as follows:

[0085] (1) This invention first monitors the agricultural irrigation environment in real time using monitoring equipment and acquires environmental and crop data; then, after data processing and analysis, it obtains analysis results and generates an irrigation strategy based on these results; next, it generates control commands based on the irrigation strategy and uses these commands to control the irrigation equipment for agricultural irrigation; finally, it acquires and analyzes historical irrigation data to generate an adaptive strategy, and then makes adaptive adjustments based on this adaptive strategy to optimize the irrigation strategy. This invention acquires the aforementioned environmental and crop data and analyzes some important conditions affecting crop growth, as well as the relationship and degree of influence between these conditions and crops, and generates an irrigation strategy for controlling agricultural irrigation; this irrigation strategy includes several influencing factors affecting agricultural irrigation, therefore, controlling the irrigation equipment with this irrigation strategy can greatly improve the accuracy of irrigation, and by controlling water and fertilizer amounts, it can meet all the necessary and optimal growth environment required for crop growth, thereby improving agricultural irrigation efficiency, reducing resource waste, and increasing crop yield.

[0086] (2) In agricultural irrigation, this invention uses a combination of ZigBee and LoRaWAN technologies for network transmission. ZigBee technology is used for short-range wireless communication, while LoRaWAN technology is used for long-range wireless communication. The combination of the two can achieve data transmission coverage within agriculture or between farms and can also adapt to various distance requirements. On the other hand, LoRaWAN technology has high anti-interference ability and signal penetration ability, making it suitable for complex agricultural environments. Its combination with ZigBee technology can establish a more robust network in a local area, ensuring reliable data transmission and stability, thereby realizing flexible, efficient, and low-cost intelligent irrigation management and providing better communication support for agricultural production.

[0087] (3) This invention uses a multi-protocol gateway processor as an intermediate node between the first sensor network node and the second sensor network node to provide data conversion and transmission between ZigBee and LoRaWAN. It supports the protocols used by both technologies, allowing heterogeneous nodes to communicate to complete the conversion between different protocols. It also supports bidirectional transparent transmission between heterogeneous nodes, making data conversion faster and solving the problems of data congestion and untimely conversion. Furthermore, it establishes a node authentication and encrypted transmission mechanism to identify the identity of network nodes and uses a two-way non-repudiation digital signature mechanism to establish a secure channel. The authentication of network nodes enhances data security, while the two-way non-repudiation digital signature... The name recognition mechanism effectively verifies data integrity and identity authentication, ensuring that neither party can deny sent or received data during interaction. Furthermore, it employs symmetric encryption on top of authentication, using the same key for both encryption and decryption (these are inverse operations). This symmetric encryption has lower overhead compared to other encryption algorithms, making it more suitable for the sensor application in this embodiment. A key pre-storage mechanism further reduces the risk of key leakage during network transmission. Additionally, random numbers are used as random step sizes during encryption and decryption, making the encryption algorithm a variable operation, increasing the difficulty of cracking the algorithm and thus improving data security.

[0088] (4) In agricultural irrigation, this invention employs energy conversion systems such as solar energy, thermal energy, and wind energy to convert the acquired natural resources such as solar energy, thermal energy, and wind energy into electrical energy for storage. This electrical energy is then used as a backup energy source when the power supply to the agricultural irrigation system is insufficient, thereby ensuring that irrigation equipment and IoT devices can operate normally without being affected by power outages. On the other hand, this invention also divides thermal energy into two parts: one part is used to convert into electrical energy, and the other part is used for storage. When the temperature difference (temperature change) of the current agricultural irrigation environment exceeds a set temperature difference threshold, the first part of the thermal energy is released to provide thermal energy to the agricultural irrigation environment, thereby ensuring that the growth of crops is not affected by temperature changes. Thus, this invention utilizes the above-mentioned energy conversion system to realize the conversion of natural resources into electrical energy and further ensures the power supply for irrigation, thereby enhancing the automated operation and data transmission of agricultural irrigation. It also increases crop yield to a certain extent through the storage of thermal energy.

[0089] (5) This invention obtains environmental and crop data by real-time monitoring of the agricultural irrigation environment and generates irrigation strategies. These strategies are used to precisely control crop growth, water and fertilizer application, thereby achieving comprehensive and accurate crop irrigation. By combining ZigBee and LoRaWAN technologies in agricultural irrigation for network transmission, reliable data transmission and stability are ensured, thereby achieving flexible, efficient, and low-cost intelligent irrigation management and providing better communication support for agricultural production. By using energy conversion systems such as solar, thermal, and wind energy in agricultural irrigation, natural resources are converted into electrical energy, further ensuring the power supply for irrigation. This enhances the automated operation and data transmission of agricultural irrigation and improves crop yield to a certain extent by storing thermal energy. By analyzing the relationship between soil conditions, meteorological conditions, and crop growth status, the required amount of irrigation water and fertilizer for crop growth is determined, thereby ensuring that crops receive the most accurate irrigation amount, saving resources, and improving irrigation efficiency and crop yield. Attached Figure Description

[0090] To better understand and implement this application, the technical solution is described in detail below with reference to the accompanying drawings.

[0091] Figure 1 A flowchart illustrating the steps of an IoT-based automated agricultural irrigation method provided in this application embodiment;

[0092] Figure 2 This is a schematic diagram of an IoT-based automated agricultural irrigation system provided in an embodiment of this application. Detailed Implementation

[0093] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, exemplary embodiments will be described in detail below, examples of which are illustrated in the accompanying drawings. In the following description relating to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of methods and systems consistent with some aspects of this application as detailed in the appended claims.

[0094] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to any and all possible combinations comprising one or more of the associated listed items.

[0095] The following detailed description of the specific implementation methods, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided in detail.

[0096] Example 1

[0097] Please see Figure 1 This application provides an automated agricultural irrigation method based on the Internet of Things, comprising the following steps:

[0098] Real-time monitoring of agricultural irrigation environment and acquisition of environmental and crop data;

[0099] The environmental data and crop data are processed and analyzed to generate irrigation strategies.

[0100] Based on the irrigation strategy, control commands are generated and used to control the irrigation equipment for agricultural irrigation.

[0101] Acquire and analyze historical irrigation data to generate adaptive strategies;

[0102] The irrigation strategy is adaptively adjusted according to the adaptive strategy to optimize it.

[0103] The environmental data includes soil conditions, meteorological conditions, irrigation conditions, and equipment conditions;

[0104] The crop data includes growth conditions, growth factors, and growth status;

[0105] Generating the irrigation strategy includes the following steps:

[0106] A first relationship is established based on the soil conditions and the crop data;

[0107] A second relationship is established based on the meteorological conditions and the crop data;

[0108] Establish a third relation based on the first and second relations;

[0109] An irrigation strategy is generated based on the third relation.

[0110] It should be noted that the adaptive strategy described in this application can identify patterns of change through historical data and provide real-time feedback. By summarizing the impact of different seasons on crop growth stages, it can make adaptive adjustments, thereby optimizing the irrigation strategy and improving its accuracy.

[0111] Specifically, existing agricultural irrigation technologies cannot precisely control the amount of irrigation water and fertilizer used, which restricts crop growth and increases resource waste. Therefore, to solve the above problems, this application first uses monitoring equipment to monitor the agricultural irrigation environment in real time and acquire environmental and crop data; then, after data processing and analysis, the analysis results are obtained, and an irrigation strategy is generated based on the analysis results; then, control commands are generated based on the irrigation strategy to control the irrigation equipment for agricultural irrigation; finally, historical irrigation data is acquired and analyzed to generate an adaptive strategy, and then adaptive adjustments are made based on the adaptive strategy to optimize the above irrigation strategy. This application generates an irrigation strategy for controlling agricultural irrigation by acquiring the aforementioned environmental and crop data and analyzing some important conditions affecting crop growth, as well as the relationship and degree of influence between these conditions and crops. This irrigation strategy includes several influencing factors affecting agricultural irrigation. Therefore, controlling irrigation equipment with this irrigation strategy can greatly improve the accuracy of irrigation and meet all the necessary and optimal growth environment required for crop growth by controlling water consumption and fertilizer application, thereby improving agricultural irrigation efficiency, reducing resource waste, and increasing crop yield.

[0112] It should be noted that the irrigation equipment in this application includes, but is not limited to, a main water supply pipe, a water pump, a solenoid valve, several water spray pipes, and a fertilizer supply device. Since this application mainly focuses on agricultural irrigation methods, the irrigation equipment can be selected according to the specific application scenario. This embodiment does not make specific limitations here. However, it can be understood that other irrigation equipment besides the irrigation equipment listed above is also within the protection scope of this application.

[0113] It is understood that the above-mentioned agricultural irrigation can refer not only to farmland, but also to farms, depending on the specific application scenario. In this embodiment, no specific limitation is made to agriculture.

[0114] In one embodiment provided in this application, the soil conditions include the degree of salinization, water content, water holding capacity, and soil fertility; the meteorological conditions include temperature, humidity, light intensity, geographical data, and meteorological data; the irrigation conditions include water level, water quantity, water quality, and pests and diseases; the equipment conditions include irrigation equipment, operating status, and degree of aging; furthermore, the geographical data includes the latitude and longitude, altitude, and topographic features (such as hills, plains, rivers, mountains, or plateaus) of the agricultural irrigation environment (farmland / farm); the meteorological data includes precipitation (such as rain and snow), sunshine hours, weather phenomena (such as sunny days, cloudy days, rainy days, snowy days), seasonal changes, and wind direction and speed.

[0115] Specifically, because soil conditions play a crucial role in crop growth, this application analyzes the soil conditions of farmland / farms, primarily determining whether soil salinity exceeds standards, whether water content and water holding capacity are within normal ranges, and whether soil fertility can sustain crop growth. Furthermore, since meteorological conditions, as an objective factor, also influence crop growth to some extent, this application analyzes meteorological conditions such as temperature and humidity, sunlight, latitude and longitude, altitude, precipitation, and weather phenomena. Irrigation conditions, another factor affecting crop growth, are analyzed by examining irrigation water levels and volumes, and monitoring water quality and pest and disease conditions to obtain optimal data for crop growth. Equipment conditions mainly involve data related to irrigation equipment; analyzing this data reveals the operational status and aging of the irrigation equipment, avoiding equipment errors or control failures from the perspective of irrigation equipment, and ensuring precise irrigation for crops. This application analyzes multiple conditions included in the above environmental data, dissects multiple external environmental factors affecting crop growth and correlates them with crop growth, then uses this correlation to generate subsequent irrigation strategies, thereby ensuring precise control over crop growth.

[0116] In one embodiment provided in this application, the crop data includes growth conditions that primarily represent the essential growth requirements of crops, such as water requirement, fertilizer requirement, light intensity, soil requirements, water quality requirements, planting time, and climate (e.g., seasonal changes can lead to crop replacement, and light intensity can affect the synthesis of nutrients within the growth factors). The growth factors primarily refer to the essential nutrients for crop growth; the content of these nutrients reflects the crop's growth status and changes in soil water and fertilizer conditions. These include nitrogen, phosphorus, potassium, and trace elements such as iron and zinc. The growth status mainly represents the daily / monthly changes in the crop's growth condition, such as seedling height, flowering status, fruit setting, fruit ripening status, and leaf and branch growth, reflecting the growth status exhibited by the crop at different growth stages. It should be noted that pests and diseases in the irrigation conditions within the environmental data can also affect crop growth to some extent; therefore, this embodiment also considers the aforementioned irrigation conditions as one of the factors for judging growth status.

[0117] Specifically, crop data mainly represents data reflecting changes in crop growth. It uses growth conditions to determine the crop's required living environment, the content of various nutrients in growth factors to reflect changes in growth conditions and the aforementioned environmental data, and further, growth status to demonstrate the crop's growth state at multiple stages. Changes in growth status reflect the impact of the aforementioned growth conditions and environmental data on the crop. This embodiment uses three changing factors—growth conditions, growth factors, and growth status—to represent the changes in crops during the growth process. It also establishes a link between these three changing factors and environmental data such as soil conditions, meteorological conditions, and irrigation conditions, making the data more complete and reliable, thereby providing the most accurate data support for subsequent irrigation strategies.

[0118] In one embodiment provided in this application, real-time monitoring of the agricultural irrigation environment specifically includes:

[0119] Multiple sensors, including environmental sensors and crop sensors, are deployed around the agricultural irrigation environment.

[0120] The first sensor network node is established using ZigBee technology;

[0121] Deploy LoRaWAN gateways in the periphery / center of agricultural irrigation environments;

[0122] A second sensor network node is established using LoRaWAN technology;

[0123] Establish a remote control terminal, including a cloud server / local control center;

[0124] Specifically, the first sensor network node establishes a network connection with the second sensor network node; the second sensor network node establishes a network connection with the remote control terminal.

[0125] The first sensor network node is used to monitor and collect data;

[0126] The second sensor network node is used to receive data sent by the first sensor network node and transmit the data to the remote control terminal via the LoRaWAN protocol;

[0127] The remote control terminal is used to receive and process data from the second sensor network node, and to analyze and store the data;

[0128] The environmental sensors include, but are not limited to, salinity sensors, moisture content sensors, water holding capacity sensors, soil fertility sensors, temperature sensors, humidity sensors, light sensors, water level sensors, water quantity sensors, water quality sensors, and rain gauges.

[0129] The crop sensors include, but are not limited to, nutrient element sensors and growth status sensors.

[0130] It should be noted that the selection of the environmental sensors is related to the aforementioned environmental data. Each data type contained in the environmental data requires a corresponding sensor for detection and data acquisition. The specific sensor selected depends on the type of environmental data and is not specifically limited in this embodiment. Similarly, the selection of crop sensors is also related to the aforementioned crop data. Each data type contained in the crop data requires a corresponding sensor for detection and data acquisition. Nutrient element sensors and growth status sensors may not be called by these names in the prior art. They are simply a general term for multiple data types in crop data in this embodiment. This embodiment only limits their function and uses them as a type of sensor for detecting crop nutrient elements and growth status. Therefore, any sensor that can detect crop nutrient elements (such as nitrogen, phosphorus, potassium, and trace elements such as iron and zinc) and growth status (such as seedling height, flowering, fruiting, fruit ripening, and branch and leaf growth) is called a "nutrient element sensor" and a "growth status sensor". For example, nutrient element sensors can be selected from spectral sensors, ion-selective electrode sensors, conductivity sensors, or chemical sensors; while growth status sensors can be selected from spectral sensors, infrared sensors, etc.

[0131] Specifically, this embodiment employs a combination of ZigBee and LoRaWAN technologies for network transmission in agricultural irrigation. ZigBee is used for short-range wireless communication, while LoRaWAN is used for long-range wireless communication. This combination enables data transmission coverage within farmland or between farms, adapting to various distance requirements. It should be noted that the two technologies already include each other's communication protocols, thus eliminating the need for additional protocols or devices as intermediate nodes. However, if an intermediate node is required, a ZigBee-LoRaWAN coordinator or an integrated chip supporting both ZigBee and LoRaWAN communication capabilities can be used to establish network communication. Furthermore, LoRaWAN technology possesses high anti-interference and signal penetration capabilities, making it suitable for complex agricultural environments. Its combination with ZigBee technology can establish a more robust network within a local area, ensuring reliable data transmission and stability. This enables flexible, efficient, and low-cost intelligent irrigation management, providing better communication support for agricultural production.

[0132] Although the ZigBee and LoRaWAN technologies mentioned above already include each other's protocols, during data transmission, if the data volume is too large, there may be data congestion caused by untimely data conversion and data security issues caused by data leakage. Therefore, in order to solve the above data congestion and data security issues, in one embodiment provided in this application, a multi-protocol gateway processor is used as the intermediate node between the first sensor network node and the second sensor network node, which includes a protocol conversion layer, a protocol support layer and a data processing layer.

[0133] The protocol conversion layer is used to convert the protocols used by ZigBee and LoRaWAN into a unified communication format;

[0134] The protocol support layer has the capability to support both the ZigBee and LoRaWAN protocols.

[0135] The data processing layer is used for receiving and forwarding data;

[0136] The protocol support layer includes a data transmission protocol frame format and a node authentication and encrypted transmission mechanism.

[0137] The data transmission protocol frame format is used to uniformly address all nodes and set the destination address to a unified address. Its communication frame format is as follows: Frame header: 2 bytes; ACK confirmation bit: 1 byte; Source address: 8 bytes; Destination address: 2 bytes; Data type: 1 byte; Data: 2 bytes; CRC check: 1 byte;

[0138] The node authentication and encrypted transmission mechanism is used to identify the identity of network nodes and establish a secure channel using a two-way non-repudiation digital signature mechanism; it is also used to encrypt data using symmetric encryption technology based on identity authentication and to store the key using a key pre-storage mechanism.

[0139] The key pre-store mechanism is specifically as follows:

[0140] An initial key is pre-stored in the node;

[0141] Store backups of the initial keys for all nodes in the network's base stations;

[0142] When the network encrypts data, nodes and base stations use their respective stored keys to encrypt and decrypt.

[0143] In the encryption and decryption process, random numbers are used as random step sizes to control the step size of data displacement during encryption.

[0144] Specifically, this application uses a multi-protocol gateway processor as an intermediate node between the first sensor network node and the second sensor network node to provide data conversion and transmission between ZigBee and LoRaWAN. It supports the protocols used by these two technologies, allowing heterogeneous nodes to communicate to complete the conversion between different protocols. It also supports bidirectional transparent transmission between heterogeneous nodes, making data conversion faster and solving the problems of data congestion and untimely conversion. Furthermore, it establishes a node authentication and encrypted transmission mechanism to identify the identity of network nodes and uses a two-way non-repudiation digital signature mechanism to establish a secure channel. The authentication of network nodes enhances data security, while the two-way non-repudiation digital signature... The name recognition mechanism effectively verifies data integrity and identity authentication, ensuring that neither party can deny sent or received data during interaction. Furthermore, it employs symmetric encryption on top of authentication, using the same key for both encryption and decryption (these are inverse operations). This symmetric encryption has lower overhead compared to other encryption algorithms, making it more suitable for the sensor application in this embodiment. A key pre-storage mechanism further reduces the risk of key leakage during network transmission. Additionally, random numbers are used as random step sizes during encryption and decryption, making the encryption algorithm a variable operation, increasing the difficulty of cracking the algorithm and thus improving data security.

[0145] Since agricultural irrigation is highly dependent on electricity, in order to avoid power outages or unstable power supply, one embodiment of this application employs an energy conversion system and a power supply system to provide power support for equipment in agricultural irrigation, including the following steps:

[0146] Solar energy is captured and converted into first electrical energy through the energy conversion system;

[0147] The system acquires thermal energy and divides it into first thermal energy and second thermal energy, stores the first thermal energy, and converts the second thermal energy into second electrical energy through the energy conversion system.

[0148] Wind energy is harvested and converted into electrical energy through the energy conversion system.

[0149] Store the first electrical energy, the second electrical energy, and the third electrical energy;

[0150] The stability of the power supply system is assessed. If the power supply is stable, the first electrical energy is used as a supplementary energy source for the power supply system. If the power supply is unstable, the second electrical energy and / or the third electrical energy are used as supplementary energy sources for the power supply system.

[0151] The energy conversion system is constructed based on the meteorological conditions and includes a solar energy subsystem, a thermal energy subsystem, and a wind energy subsystem.

[0152] The solar energy subsystem is linked to sunlight, sunshine hours, and geographic data to convert solar energy into electrical energy.

[0153] The thermal energy subsystem is linked to temperature, light, and geographic data to store thermal energy and convert it into electrical energy.

[0154] The wind energy subsystem is linked with wind direction, wind speed, and geographical data to convert wind energy into electrical energy.

[0155] Among them, the temperature difference (temperature change) of the current agricultural irrigation environment is judged based on meteorological data. If the temperature difference is greater than the set temperature difference threshold, the first heat energy is released to provide heat energy for the agricultural irrigation environment.

[0156] The temperature difference threshold is set based on historical temperature difference data and crop growth conditions.

[0157] Specifically, this application employs energy conversion systems for solar, thermal, and wind energy in agricultural irrigation. These systems convert acquired natural resources such as solar, thermal, and wind energy into electrical energy for storage. This stored electrical energy serves as backup power when the main power supply for agricultural irrigation is insufficient, ensuring that irrigation equipment and IoT devices can operate normally without being affected by power outages. The reason for using the first type of electrical energy as a supplementary energy source when the power supply is stable, and the second and / or third type when the power supply is unstable, is that among the three renewable energy sources—solar, thermal, and wind—solar energy provides the least amount of electricity when converted to electricity. Converting solar energy to electricity typically requires photovoltaic panels to directly convert sunlight into electricity. In contrast, the conversion efficiency of thermal and wind energy is generally higher than that of solar energy. Therefore, solar energy is used as a backup energy source when the main power supply is insufficient, ensuring the normal operation of irrigation equipment and IoT devices. The first source of electrical energy, used as supplementary energy when the power supply system is stable, provides an extra layer of protection without significant energy loss. Furthermore, this embodiment divides the thermal energy into two parts: one part is converted into electrical energy, and the other is stored. When the temperature difference (temperature change) in the current agricultural irrigation environment exceeds a set temperature difference threshold, the first source of thermal energy is released to provide heat to the agricultural irrigation environment, thus ensuring that crop growth is not affected by temperature changes. The set temperature difference threshold is determined based on historical temperature difference data and analysis of the relationship between temperature difference and crop growth. Therefore, this application utilizes the aforementioned energy conversion system to convert natural resources into electrical energy and further ensures the power supply for irrigation, thereby enhancing the automated operation and data transmission of agricultural irrigation. The stored thermal energy also increases crop yield to a certain extent.

[0158] It should be noted that this embodiment does not specifically limit the devices included in the energy conversion system. Any energy conversion system that can achieve the above functions and effects is within the protection scope of this embodiment.

[0159] Furthermore, the stability of the power supply system is assessed, specifically including:

[0160] The voltage fluctuations at each node in the power supply system are judged. If the voltage fluctuations exceed the set voltage range, the power supply system is judged to be unstable.

[0161] The frequency change of the power supply system is judged. If the frequency change exceeds the set frequency range, the power supply system is judged to be unstable.

[0162] The power balance among the various loads in the power supply system is judged. If an overload or underload occurs, the power supply system is judged to be unstable.

[0163] Conversely, the power supply system is considered stable.

[0164] Specifically, this embodiment determines whether the power supply system is stable by judging voltage fluctuations, frequency changes, and power balance; by monitoring and evaluating the above parameters, the stability of the power supply system can be fully and accurately understood.

[0165] In one embodiment provided in this application, the first relation is expressed as:

[0166] W1 = P * h(H - (H0 + H1 + H2));

[0167] Where W1 represents the first irrigation water and fertilizer amount; P represents the growth status of crops; h() represents the mapping function between soil conditions and crop growth conditions; H represents the degree of soil salinization; H0 represents soil moisture content; H1 represents soil water holding capacity; and H2 represents soil fertility.

[0168] Specifically, this embodiment performs a correlation analysis between soil conditions and crop growth status, establishes a mapping function between soil salinity, water content, water holding capacity and soil fertility and growth conditions, and then uses this mapping function and growth status to express the first irrigation water and fertilizer amount; the first irrigation water and fertilizer amount is used to represent the amount of irrigation water and fertilizer (including water and fertilizer) required by crops under the condition that soil conditions and crop data are the main factors.

[0169] In one embodiment provided in this application, the second relation is expressed as:

[0170] W2=P*f((F+F')-(F0+F1+F2));

[0171] Where W2 represents the second irrigation water and fertilizer amount; P represents the crop growth status; f() represents the mapping function between meteorological conditions and crop growth conditions; F represents meteorological data; F' represents geographical data; F0 represents temperature; F1 represents humidity; and F2 represents light intensity.

[0172] Specifically, this embodiment performs a correlation analysis between meteorological conditions and crop growth status, establishes a mapping function between temperature, humidity, light, geographical data and meteorological data in meteorological conditions and growth conditions, and then uses the mapping function and growth status to express the second irrigation water and fertilizer amount; the second irrigation water and fertilizer amount is used to represent the amount of irrigation water and fertilizer required by crops under the condition that meteorological conditions and crop data are the main factors.

[0173] In one embodiment provided in this application, the third relation is expressed as: W = W1 + W2;

[0174] Where W represents the total amount of irrigation water and fertilizer required for crop growth; W1 represents the first amount of irrigation water and fertilizer; and W2 represents the second amount of irrigation water and fertilizer.

[0175] Specifically, the third relation combines the first and second relations to calculate the total amount of irrigation water and fertilizer required for crop growth. The total amount of irrigation water and fertilizer is obtained by conducting an overall analysis with meteorological and soil conditions as influencing factors, which can reflect the relationship between crop growth status and changes in meteorological and soil conditions.

[0176] It should be noted that the third relation only represents the required amount of irrigation water and fertilizer. The irrigation strategy generated based on the third relation also needs to take into account the irrigation time and irrigation equipment. Therefore, deriving the third relation is not the same as generating an irrigation strategy. Only by taking irrigation water and fertilizer, irrigation time, and irrigation equipment as factors together can an irrigation strategy be finally generated.

[0177] In summary, this application achieves comprehensive and accurate crop irrigation by acquiring environmental and crop data through real-time monitoring of the agricultural irrigation environment and generating irrigation strategies. These strategies enable precise control of crop growth, water and fertilizer application, and pesticide use. By combining ZigBee and LoRaWAN technologies for network transmission in agricultural irrigation, reliable data transmission and stability are ensured, enabling flexible, efficient, and low-cost intelligent irrigation management and providing better communication support for agricultural production. Furthermore, the use of energy conversion systems such as solar, thermal, and wind power in agricultural irrigation converts natural resources into electricity, further guaranteeing the power supply for irrigation and enhancing the automation and data transmission of agricultural irrigation. The stored thermal energy also increases crop yield to some extent. Finally, by analyzing the relationship between soil conditions, meteorological conditions, and crop growth status, the required irrigation water and fertilizer amounts for crop growth are determined, ensuring the most accurate irrigation amounts for crops, saving resources, and improving irrigation efficiency and crop yield.

[0178] In summary, the IoT-based automated agricultural irrigation method described in this application can greatly improve irrigation efficiency, reduce resource waste, and increase yield.

[0179] Example 2

[0180] Please see Figure 2 This application provides an automated agricultural irrigation system based on the Internet of Things, including a sensor module, a data communication module, a central control module, an adaptive optimization module, and an energy conversion module;

[0181] The sensor module is used to deploy several sensors and monitor the agricultural irrigation environment in real time to obtain environmental data and crop data.

[0182] The data communication module is used to establish a data transmission channel and encrypt the network connection;

[0183] The central control module is used to process and analyze the environmental data and the crop data and generate irrigation strategies; it also generates control commands based on the irrigation strategies and uses the control commands to control the irrigation equipment for agricultural irrigation.

[0184] The adaptive optimization module is used to acquire and analyze historical irrigation data to generate an adaptive strategy, and to make adaptive adjustments based on the adaptive strategy to optimize the irrigation strategy.

[0185] The energy conversion module is used to convert solar, wind and thermal energy into electrical energy and provide power support for equipment in agricultural irrigation;

[0186] The environmental data includes soil conditions, meteorological conditions, irrigation conditions, and equipment conditions;

[0187] The crop data includes growth conditions, growth factors, and growth status;

[0188] Generating the irrigation strategy includes the following steps:

[0189] A first relationship is established based on the soil conditions and the crop data;

[0190] A second relationship is established based on the meteorological conditions and the crop data;

[0191] Establish a third relation based on the first and second relations;

[0192] An irrigation strategy is generated based on the third relation.

[0193] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0194] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0195] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0196] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. An automated agricultural irrigation method based on the Internet of Things, characterized in that: Includes the following steps: Real-time monitoring of agricultural irrigation environment and acquisition of environmental and crop data; The environmental data and crop data are processed and analyzed to generate irrigation strategies. Based on the irrigation strategy, control commands are generated and used to control the irrigation equipment for agricultural irrigation. Acquire and analyze historical irrigation data to generate adaptive strategies; The irrigation strategy is adaptively adjusted according to the adaptive strategy to optimize the irrigation strategy. The environmental data includes soil conditions, meteorological conditions, irrigation conditions, and equipment conditions; The crop data includes growth conditions, growth factors, and growth status; Generating the irrigation strategy includes the following steps: A first relationship is established based on the soil conditions and the crop data; A second relationship is established based on the meteorological conditions and the crop data; Establish a third relation based on the first and second relations; An irrigation strategy is generated based on the third relation. The third relation is expressed as: ; Where W represents the total amount of irrigation water and fertilizer required for crop growth; This indicates the amount of water and fertilizer used for the first irrigation. This indicates the amount of water and fertilizer used for the second irrigation. The first relation is expressed as: ; in, denoted by , where represents the first irrigation water and fertilizer amount; P represents the crop growth status; h() represents the mapping function between soil conditions and crop growth conditions; H represents the degree of soil salinization. Indicates soil moisture content; Indicates soil water holding capacity; Indicates soil fertility; The second relation is expressed as: ; in, The amount of water and fertilizer used for the second irrigation is represented by ; P represents the growth status of the crop; f() represents the mapping function between meteorological conditions and crop growth conditions; F represents meteorological data. Represents geographic data; Indicates temperature; Indicates humidity; It indicates light.

2. The automated agricultural irrigation method based on the Internet of Things according to claim 1, characterized in that: The soil conditions include the degree of salinization, water content, water holding capacity, and soil fertility; the meteorological conditions include temperature, humidity, light intensity, geographical data, and meteorological data; the irrigation conditions include water level, water quantity, water quality, and pests and diseases; and the equipment conditions include irrigation equipment, operating status, and degree of aging. The geographic data includes the latitude, longitude, altitude, and topographic features of the agricultural irrigation environment; the meteorological data includes precipitation, sunshine hours, weather phenomena, seasonal changes, and wind direction and speed.

3. The automated agricultural irrigation method based on the Internet of Things according to claim 1, characterized in that: In the crop data, the growth conditions represent the growth requirements necessary for crop growth, including water requirement, fertilizer requirement, light requirement, soil requirements, water quality requirements, planting time, and climate environment; the growth factors represent the nutrient elements necessary for crop growth, including nitrogen, phosphorus, potassium, iron, and zinc; and the growth status represents the growth state exhibited by the crop at different growth stages.

4. The automated agricultural irrigation method based on the Internet of Things according to claim 1, characterized in that: Real-time monitoring of the agricultural irrigation environment includes: Multiple sensors, including environmental sensors and crop sensors, are deployed around the agricultural irrigation environment. The first sensor network node is established using ZigBee technology; Deploy LoRaWAN gateways in the periphery / center of agricultural irrigation environments; A second sensor network node is established using LoRaWAN technology; Establish a remote control terminal, including a cloud server / local control center; Specifically, the first sensor network node establishes a network connection with the second sensor network node; the second sensor network node establishes a network connection with the remote control terminal. The first sensor network node is used to monitor and collect data; The second sensor network node is used to receive data sent by the first sensor network node and transmit the data to the remote control terminal via the LoRaWAN protocol; The remote control terminal is used to receive and process data from the second sensor network node, and to analyze and store the data; The environmental sensors include a salinity sensor, a moisture content sensor, a water holding capacity sensor, a soil fertility sensor, a temperature sensor, a humidity sensor, a light sensor, a water level sensor, a water quantity sensor, a water quality sensor, and a rain gauge. The crop sensors include nutrient element sensors and growth status sensors.

5. The automated agricultural irrigation method based on the Internet of Things according to claim 4, characterized in that: A multi-protocol gateway processor is used as an intermediate node between the first sensor network node and the second sensor network node, and it includes a protocol conversion layer, a protocol support layer and a data processing layer. The protocol conversion layer is used to convert the protocols used by ZigBee and LoRaWAN into a unified communication format; The protocol support layer has the capability to support both ZigBee and LoRaWAN protocols; The data processing layer is used for receiving and forwarding data; The protocol support layer includes a data transmission protocol frame format and a node authentication and encrypted transmission mechanism. The data transmission protocol frame format is used to uniformly address all nodes and set the destination address to a unified address. Its communication frame format is as follows: Frame header: 2 bytes; ACK confirmation bit: 1 byte; Source address: 8 bytes; Destination address: 2 bytes; Data type: 1 byte; Data: 2 bytes; CRC check: 1 byte; The node authentication and encrypted transmission mechanism is used to identify the identity of network nodes and establish a secure channel using a two-way non-repudiation digital signature mechanism; it is also used to encrypt data using symmetric encryption technology based on identity authentication and to store the key using a key pre-storage mechanism. The key pre-store mechanism is as follows: An initial key is pre-stored in the node; Store backups of the initial keys for all nodes in the network's base stations; When the network encrypts data, nodes and base stations use their respective stored keys to encrypt and decrypt. In the encryption and decryption process, random numbers are used as random step sizes to control the step size of data displacement during encryption.

6. The automated agricultural irrigation method based on the Internet of Things according to claim 1, characterized in that: Providing electrical support for equipment in agricultural irrigation using energy conversion and power supply systems includes the following steps: Solar energy is captured and converted into first electrical energy through the energy conversion system; The system acquires thermal energy and divides it into first thermal energy and second thermal energy, stores the first thermal energy, and converts the second thermal energy into second electrical energy through the energy conversion system. Wind energy is harvested and converted into electrical energy through the energy conversion system. Store the first electrical energy, the second electrical energy, and the third electrical energy; The stability of the power supply system is assessed. If the power supply is stable, the first electrical energy is used as a supplementary energy source for the power supply system. If the power supply is unstable, the second electrical energy and / or the third electrical energy are used as supplementary energy sources for the power supply system. The energy conversion system is constructed based on the meteorological conditions and includes a solar energy subsystem, a thermal energy subsystem, and a wind energy subsystem. The solar energy subsystem is linked to sunlight, sunshine hours, and geographic data to convert solar energy into electrical energy. The thermal energy subsystem is linked to temperature, light, and geographic data to store thermal energy and convert it into electrical energy. The wind energy subsystem is linked with wind direction, wind speed, and geographical data to convert wind energy into electrical energy. Among them, the temperature difference of the current agricultural irrigation environment is determined based on meteorological data. If the temperature difference is greater than the set temperature difference threshold, the first heat energy is released to provide heat energy for the agricultural irrigation environment. The temperature difference threshold is set based on historical temperature difference data and crop growth conditions.

7. The automated agricultural irrigation method based on the Internet of Things according to claim 6, characterized in that: Assessing the stability of the power supply system includes: The voltage fluctuations at each node in the power supply system are judged. If the voltage fluctuations exceed the set voltage range, the power supply system is judged to be unstable. The frequency change of the power supply system is judged. If the frequency change exceeds the set frequency range, the power supply system is judged to be unstable. The power balance among the various loads in the power supply system is judged. If an overload or underload occurs, the power supply system is judged to be unstable. Conversely, the power supply system is considered stable.

8. An automated agricultural irrigation system based on the Internet of Things, applied to the automated agricultural irrigation method as described in any one of claims 1-7, characterized in that: It includes a sensor module, a data communication module, a central control module, an adaptive optimization module, and an energy conversion module; The sensor module is used to deploy several sensors and monitor the agricultural irrigation environment in real time to obtain environmental data and crop data. The data communication module is used to establish a data transmission channel and encrypt the network connection; The central control module is used to process and analyze the environmental data and the crop data and generate irrigation strategies; it also generates control commands based on the irrigation strategies and uses the control commands to control the irrigation equipment for agricultural irrigation. The adaptive optimization module is used to acquire and analyze historical irrigation data to generate an adaptive strategy, and to make adaptive adjustments based on the adaptive strategy to optimize the irrigation strategy. The energy conversion module is used to convert solar, wind and thermal energy into electrical energy and provide power support for equipment in agricultural irrigation; The environmental data includes soil conditions, meteorological conditions, irrigation conditions, and equipment conditions; The crop data includes growth conditions, growth factors, and growth status; Generating the irrigation strategy includes the following steps: A first relationship is established based on the soil conditions and the crop data; A second relationship is established based on the meteorological conditions and the crop data; Establish a third relation based on the first and second relations; An irrigation strategy is generated based on the third relation.

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