Automatic plant irrigation management method and system applying Internet of Things and remote monitoring

Abstract

The invention discloses an automatic plant irrigation management method and system applying the Internet of Things and remote monitoring, and belongs to the technical field of Internet of Things and automatic irrigation. The sensor data uploaded by the plurality of sensors are acquired through the Internet of Things, the automatic irrigation strategy is generated and executed according to the environment data, the automatic irrigation strategy is set according to the soil real-time data detected by the sensors, the irrigation amount and the irrigation opportunity can be accurately controlled, the optimal humidity needed by plant growth is ensured, and the irrigation efficiency is improved. Excessive irrigation or insufficient irrigation is avoided, so that water resources are saved, and the irrigation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of Internet of Things technology and automatic irrigation technology, and in particular to a method and system for automatic plant irrigation management using the Internet of Things and remote monitoring. Background Art

[0002] With the rapid development of Internet of Things (IoT) technology, smart agriculture has gradually become an important direction of global agricultural innovation. IoT technology connects various sensors, actuators and control systems to the Internet, making data collection, monitoring and control in the agricultural production process more accurate and efficient. Especially in the field of plant irrigation, by combining environmental monitoring and automatic control technology, precise irrigation can be achieved, the use of water resources can be optimized, and agricultural output and quality can be improved. The widespread application of sensor technology, wireless communication, data storage and processing technology, and automatic control systems in smart agriculture provides a new solution for agricultural irrigation.

[0003] Traditional irrigation methods mainly rely on manual intervention or timer-based automatic irrigation systems. Manual intervention is not only labor-intensive, but also easily affected by subjective factors. It is often impossible to accurately irrigate according to the actual needs of plants, resulting in water waste or crop water shortage. Although the timer-based automatic irrigation system can irrigate at the preset time, it cannot be adjusted according to real-time environmental changes such as soil moisture and weather changes, resulting in excessive or insufficient irrigation, which not only wastes water resources but also reduces irrigation efficiency. Summary of the invention

[0004] In order to solve the problems of the prior art, the embodiment of the present invention provides a method and system for automatic plant irrigation management using the Internet of Things and remote monitoring. The technical solution is as follows:

[0005] In one aspect, a method for automatic plant irrigation management using the Internet of Things and remote monitoring is provided, the method comprising:

[0006] Through the Internet of Things, sensor data uploaded by multiple sensors are obtained;

[0007] Preprocessing the sensor data to obtain environmental data;

[0008] generating a visualization strategy and an automatic irrigation strategy according to the environmental data;

[0009] The visualization strategy and the automatic irrigation strategy are executed.

[0010] Optionally, the method further includes:

[0011] Preset multiple monitoring nodes;

[0012] According to the monitoring requirements of the multiple monitoring nodes, corresponding multiple sensors are respectively set, and the multiple sensors are connected through the Internet of Things.

[0013] Optionally, the preprocessing the sensor data to obtain the environmental data includes:

[0014] Set the gain factor and offset corresponding to the sensor;

[0015] Preprocessing the sensor data uploaded by the sensor according to the gain coefficient and the offset;

[0016] The preprocessed sensor data is converted from digital to analog to obtain environmental data corresponding to the sensor.

[0017] Optionally, generating the visualization strategy according to the environmental data includes:

[0018] According to the complexity and linear relationship of the environmental data, different fitting algorithms are adopted;

[0019] According to the fitting algorithm, the environmental data is fitted to obtain visualization data;

[0020] The visualization data is displayed.

[0021] Optionally, generating the automatic irrigation strategy according to the environmental data includes:

[0022] Set target environment data;

[0023] According to the target environmental data, setting the automatic irrigation frequency;

[0024] The automatic irrigation strategy is generated and executed according to the target environmental data and the target irrigation frequency.

[0025] Optionally, after executing the automatic irrigation strategy, the method further includes:

[0026] Obtain plant growth trend parameters;

[0027] The target environmental data and the target irrigation frequency are corrected in real time according to the plant growth trend parameters.

[0028] On the other hand, an automatic plant irrigation management system using the Internet of Things and remote monitoring is provided, the system comprising a plurality of sensor modules, a visualization module, and an automatic irrigation module, wherein:

[0029] The plurality of sensor modules are used for:

[0030] Through the Internet of Things, sensor data uploaded by multiple sensors are obtained;

[0031] Preprocessing the sensor data to obtain environmental data;

[0032] The visualization module is used to generate a visualization strategy according to the environmental data and execute the visualization strategy;

[0033] The automatic irrigation module is used to generate an automatic irrigation strategy according to the environmental data and execute the automatic irrigation strategy.

[0034] Optionally, the sensor module specifically includes:

[0035] Sensor, used to obtain sensor data;

[0036] Signal conditioning modules for:

[0037] Set the gain factor and offset corresponding to the sensor;

[0038] Preprocessing the sensor data uploaded by the sensor according to the gain coefficient and the offset;

[0039] An A / D conversion module is used to perform digital-to-analog conversion on the preprocessed sensor data to obtain environmental data corresponding to the sensor;

[0040] The data storage and sending module is used to store and upload the environmental data.

[0041] Optionally, the visualization module is specifically used for:

[0042] According to the complexity and linear relationship of the environmental data, different fitting algorithms are adopted;

[0043] According to the fitting algorithm, the environmental data is fitted to obtain visualization data;

[0044] The visualization data is displayed.

[0045] Optionally, the automatic irrigation module is specifically used for:

[0046] Set target environment data;

[0047] According to the target environmental data, setting the automatic irrigation frequency;

[0048] The automatic irrigation strategy is generated and executed according to the target environmental data and the target irrigation frequency.

[0049] The technical solution provided by the embodiment of the present invention has the following beneficial effects:

[0050] Through the Internet of Things, sensor data uploaded by multiple sensors are obtained, and automatic irrigation strategies are generated and executed based on environmental data. The real-time soil data detected by the sensors is used to set automatic irrigation strategies. The irrigation amount and timing can be accurately controlled to ensure the optimal humidity required for plant growth, avoid over-irrigation or under-irrigation, thereby saving water resources and improving irrigation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0052] Figure 1 This is a flow chart of a method for automatic plant irrigation management using the Internet of Things and remote monitoring provided by an embodiment of the present invention;

[0053] Figure 2 This is a flow chart of a method for automatic plant irrigation management using the Internet of Things and remote monitoring provided by an embodiment of the present invention;

[0054] Figure 3 It is a schematic diagram of an automatic plant irrigation management system using the Internet of Things and remote monitoring provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0056] The purpose of the present invention is to provide an accurate and intelligent plant irrigation management system by combining Internet of Things technology, automatic control system and sensor technology, aiming to achieve real-time monitoring and accurate control of the plant irrigation process. The system can automatically adjust irrigation parameters according to real-time environmental data, optimize the use of water resources, avoid water resource waste and irrigation inaccuracy in traditional irrigation methods, improve irrigation efficiency, and provide users with remote monitoring and data analysis functions, thereby improving the intelligence level of agricultural production, water-saving efficiency and crop growth quality. In order to achieve the above purpose, the embodiment of the present invention provides a plant automatic irrigation management method and system using the Internet of Things and remote monitoring, which are as follows:

[0057] Reference Figure 1As shown, a method for automatic plant irrigation management using the Internet of Things and remote monitoring is provided, comprising:

[0058] 101. Obtain sensor data uploaded by multiple sensors through the Internet of Things;

[0059] 102. Preprocess the sensor data to obtain environmental data;

[0060] 103. Generate visualization strategies and automatic irrigation strategies based on environmental data;

[0061] 104. Implement visualization strategies and automatic irrigation strategies.

[0062] Among them, environmental data includes temperature, humidity, light intensity and soil moisture content.

[0063] Optionally, the method further includes:

[0064] Preset multiple monitoring nodes;

[0065] According to the monitoring requirements of multiple monitoring nodes, multiple corresponding sensors are set up respectively, and the multiple sensors are connected through the Internet of Things.

[0066] Optionally, the sensor data is preprocessed to obtain environmental data including:

[0067] Set the gain factor and offset corresponding to the sensor;

[0068] According to the gain coefficient and the offset, the sensor data uploaded by the sensor is preprocessed. The process can be specifically as follows:

[0069] S out (t) = g·(S in (t)-S bias )

[0070] Among them, S out (t) represents the conditioned output signal, S in (t) represents the input signal of the sensor, g is the gain factor of signal amplification, S bias is the amount of offset removed.

[0071] The sensor data uploaded by the sensor is preprocessed through the gain coefficient and offset, ensuring that the signal output by the sensor can adapt to the input range of the A / D conversion module, thereby avoiding signal overload or distortion.

[0072] The preprocessed sensor data is converted into digital-to-analog format to obtain the environmental data corresponding to the sensor. The specific process is as follows:

[0073] The pre-processed sensor data (analog signal) is converted into a digital signal through sampling, quantization and encoding. Here, the accuracy and sampling rate of A / D conversion are crucial to the response speed and accuracy of the system. The A / D conversion process can be expressed by the following formula:

[0074]

[0075] Where D(t) is the digital signal, A(t) is the analog signal after signal conditioning, and Δ is the quantization step size.

[0076] Optionally, based on the environment data, generate a visualization strategy including:

[0077] Different fitting algorithms are adopted according to the complexity and linear relationship of environmental data;

[0078] According to the fitting algorithm, the environmental data is fitted to obtain the visual data;

[0079] Displays the data for visualization.

[0080] In practical applications, the above process can be specifically as follows:

[0081] For environmental data with linear relationships, such as temperature, humidity, etc., which are linearly related to other variables, linear fitting is adopted, and its function is:

[0082] y=kx+b

[0083] Where y is the dependent variable, x is the independent variable, k is the slope, and b is the intercept. The equation of the line that best fits the data can be found.

[0084] For complex environmental data with nonlinear relationships, curve fitting is adopted. Curve fitting algorithms include Bezier curve fitting, exponential fitting, etc.

[0085] The selection of the above curve fitting algorithm is determined according to the actual distribution form of the environmental data and the preset standard.

[0086] Before fitting the environmental data, the environmental data is also preprocessed, including filtering, data normalization and curve smoothing. Filtering helps remove noise from sensor data, data normalization converts data into a standard numerical range, and curve smoothing helps reduce the impact of short-term fluctuations and make the trend more stable.

[0087] After the data is processed, the sensor data visualization module converts it into intuitive charts so that users can quickly understand changes in environmental conditions. For example, the changing trends of temperature and humidity can be displayed through real-time updated curve charts, while the irrigation data visualization module displays the irrigation process, irrigation intensity and related control parameters through a graphical interface.

[0088] Through visualization strategies, technicians can view the soil moisture change trend corresponding to temperature changes in real time, determine whether irrigation needs to be started, and set the appropriate irrigation intensity and timing. Through data fitting algorithms and visualization technology, the monitoring platform can not only display the data collected by sensors in real time, but also predict and control environmental data through precise mathematical models, helping to optimize the irrigation process and improve water resource utilization efficiency.

[0089] The relationship between soil moisture and temperature, the fitting result is:

[0090] M(T)=0.002T 2 -1.5T+30;

[0091] Among them, M(T) represents the soil moisture content and T is the temperature. Based on this equation, the system can predict the changing trend of soil moisture content at different temperatures, thereby optimizing the irrigation plan.

[0092] The relationship between soil moisture and humidity, the fitting result is:

[0093] M(H)=0.008H 2 -1.2H+40;

[0094] Among them, M(H) represents the soil moisture content and H represents the humidity. Based on this equation, the system can predict the changing trend of soil moisture content under different humidity levels, thereby optimizing the irrigation plan.

[0095] The relationship between soil moisture and light intensity, the fitting result is:

[0096] M(L)=0.002L 2 -1.8L+10;

[0097] Among them, M(L) represents the soil moisture content and L is the light intensity. Based on this equation, the system can predict the changing trend of soil moisture content under different light intensities, thereby optimizing the irrigation plan.

[0098] Optionally, based on environmental data, automatic irrigation strategies are generated including:

[0099] Set target environment data;

[0100] Set automatic irrigation frequency according to target environmental data;

[0101] Generate and execute automatic irrigation strategies based on target environmental data and target irrigation frequency.

[0102] The target environmental data are set to target temperature, target humidity, target light intensity and target soil moisture content; the automatic irrigation frequency is set to an initial value, and during the irrigation process, the automatic irrigation frequency is corrected by the real-time temperature, real-time humidity, real-time light intensity and real-time soil moisture content;

[0103] Calculate the current temperature, current humidity, current light intensity and current soil moisture content, and the time t to reach the target temperature, target humidity, target light intensity and target soil moisture content;

[0104] The decision function for irrigation control is set as:

[0105] I(t)=f(T(t),H(t),L(t),M(t))

[0106] Where I(t) represents the intensity or switch state of irrigation at time t, T(t) is temperature, H(t) is humidity, L(t) is light intensity, and M(t) is soil moisture content;

[0107] Obtain the impact factor between T(t), H(t), and L(t), which can be obtained by weighted average method or regression analysis;

[0108] Assume that the impact factors between T(t) and H(t) and L(t) are: a1 and a2 respectively;

[0109] Assume that the influence factors between H(t) and L(t) are: b1;

[0110] The process of calculating the current temperature, the current humidity, the current light intensity and the current soil moisture content, and the time t to reach the target temperature, the target humidity, the target light intensity and the target soil moisture content can be:

[0111] According to M(T), calculate the temperature at the target soil moisture content and set the temperature as the target temperature;

[0112] According to M(H), calculate the humidity at the target soil moisture content and set the humidity as the target humidity;

[0113] According to M(L), calculate the light intensity at the target soil moisture content, and set the light intensity as the target light intensity;

[0114] According to the current temperature, predict the time t1 when the temperature reaches the target temperature;

[0115] According to the current humidity, predict the time t2 when the humidity reaches the target humidity;

[0116] According to the current light intensity, predict the time t3 when the light intensity reaches the target light intensity;

[0117] Set the time to: t = t1*(t1+t2*a1+t3*b1) / (t1+t2+t3)+t2*(t1*a1+t2+t3*b1) / (t1+t2+t3)+t1*(t1*a1+t2*b1+t3) / (t1+t2+t3);

[0118] Through the above automatic irrigation strategy, the irrigation amount is adjusted in real time according to environmental changes to optimize the use of water resources, so that in arid environments, when the soil moisture is low, a higher irrigation intensity may be required, while in humid environments, the irrigation intensity may be lower.

[0119] Preferably, the environmental data can also be uploaded to a data server and analyzed and processed by a data processing module to obtain processing results to facilitate adjustments by technical personnel;

[0120] Preferably, historical data is used to help technicians understand the long-term trend of plant growth and optimize irrigation strategies. The historical data is historical temperature, historical humidity, historical light intensity, and historical soil moisture content.

[0121] By combining real-time monitoring data with historical data analysis, the system can ensure the best growth environment for plants while maximizing water conservation.

[0122] In practical applications, taking soil moisture as an example, the above process can be specifically described as follows:

[0123] Set a target humidity value based on plant needs, which is the ideal level of soil moisture;

[0124] Soil moisture is monitored in real time through sensors. When the soil moisture is lower than the set value, the irrigation process starts. Once the soil moisture reaches the target moisture value, the irrigation stops.

[0125] Assume that the target humidity is set to H target The actual humidity value monitored is H current , the control formula of the system when performing irrigation is:

[0126] iF current <H target thenstartirrigation

[0127] The purpose of this formula is to ensure that when soil moisture falls below the target value, the irrigation system automatically starts irrigating until the target moisture is reached.

[0128] In the above frequency setting process, the interval time between each irrigation is set. The frequency control formula can be expressed as:

[0129] ifnumberofirrigations≥frequencylimitthens topirrigation

[0130] The purpose of this formula is to control the periodicity of irrigation, ensuring that the system operates at the set frequency and avoiding over-watering.

[0131] The decision on whether to start irrigation is based on the humidity setting value, frequency setting value, and real-time monitoring data. Once the soil moisture reaches the target humidity H target , the system will stop irrigation; similarly, when the set number of irrigation times is reached, the irrigation process will also stop.

[0132] In addition, you can also set up remote irrigation strategies based on automatic irrigation strategies;

[0133] The technician customizes the humidity set point and frequency set point, and the system starts or stops irrigation according to the humidity set point and frequency set point.

[0134] Assume that the user sets the target humidity H target = 60% and the irrigation frequency is twice a day, the system will start irrigation when it detects that the soil moisture is lower than 60%, and will not irrigate until the moisture returns to the set value. If the humidity at the beginning of an irrigation is 55%, and the soil moisture gradually rises to 60% through irrigation, the irrigation process will automatically stop. At this time, the system will record the number of irrigations, and if the set frequency (such as twice a day) is reached, the next irrigation will not be carried out.

[0135] Through this precise control and feedback mechanism, the system can flexibly adjust water according to environmental changes and plant needs, ensuring that irrigation is both sufficient and water-saving.

[0136] Optionally, after executing the automatic irrigation strategy, the method further includes:

[0137] Obtain plant growth trend parameters;

[0138] According to the plant growth trend parameters, the target environmental data and target irrigation frequency are corrected in real time.

[0139] Reference Figure 2 As shown, an embodiment of the present invention provides a method for automatic plant irrigation management using the Internet of Things and remote monitoring, including:

[0140] 201. The sensor module collects environmental data.

[0141] Specifically, the collected data is pre-processed by the signal conditioning module and then converted into digital signals by the A / D conversion module. The processed data is temporarily stored by the data storage and transmission module. At this time, the data is transmitted to the gateway via the wireless network, and the gateway temporarily stores the data and forwards it to the monitoring platform.

[0142] 202. After the environmental data is transmitted to the monitoring platform, the monitoring platform generates irrigation control instructions based on the environmental data.

[0143] Specifically, after the data is transmitted to the monitoring platform, the platform sends the data to the data server. The data processing module in the data server calculates and analyzes the temporarily stored data information, combines the set parameters (such as target humidity, temperature range, etc.), and generates irrigation control instructions through a preset algorithm.

[0144] This process is handled by the following calculation formula:

[0145] I control =f(H current ,H target ,F)

[0146] Among them, I control Represents the generated irrigation control instruction, H current is the current soil moisture, H target is the target humidity, and F is the irrigation frequency. The purpose of this formula is to calculate whether irrigation is needed and the intensity of control through the difference between the current humidity and the target humidity, as well as the set irrigation frequency.

[0147] Furthermore, the intensity or time of irrigation can be automatically adjusted in combination with the preset frequency.

[0148] For example, if the target humidity is 60%, the current humidity is 50%, and the set frequency is once a day, the system will generate an irrigation instruction based on this difference, which may require irrigation to start and continue for a certain period of time until the humidity reaches the target value.

[0149] 203. The irrigation instructions calculated by the data server will be sent to the control center, and the control center will further instruct the gateway controller to control the start and stop of the irrigation components according to the received instructions.

[0150] Specifically, control the opening of a water pump or a solenoid valve to complete the actual irrigation task.

[0151] 204. Dynamically adjust the irrigation process.

[0152] Assume that the current soil moisture collected by the sensor module is 45%, and the target humidity H target = 60%, and the set irrigation frequency is twice a day. According to the formula, the current irrigation instruction Icontrol It may be to start irrigation for a certain period of time until the humidity returns to the set value. The calculation process can be:

[0153] I control =f(45%,60%,2)

[0154] The system starts irrigation based on this instruction and stops irrigation after the target humidity is reached, ensuring effective water conservation.

[0155] The algorithm conversion in the data processing module integrates sensor data with set parameters to generate control instructions, achieving precise automatic irrigation management. This process not only ensures the efficient operation of the system, but also responds to environmental changes in real time, providing the best water supply for plants through flexible algorithms and control mechanisms, while avoiding water waste.

[0156] Reference Figure 3 As shown, a plant automatic irrigation management system using the Internet of Things and remote monitoring is provided. The system includes multiple sensor modules, a visualization module, and an automatic irrigation module, wherein:

[0157] Multiple sensor modules for:

[0158] Through the Internet of Things, sensor data uploaded by multiple sensors are obtained;

[0159] Preprocess the sensor data to obtain environmental data;

[0160] The visualization module is used to generate visualization strategies based on environmental data and execute visualization strategies;

[0161] The automatic irrigation module is used to generate automatic irrigation strategies based on environmental data and execute automatic irrigation strategies.

[0162] Optionally, the sensor module specifically includes:

[0163] Sensor, used to obtain sensor data;

[0164] Signal conditioning modules for:

[0165] Set the gain factor and offset corresponding to the sensor;

[0166] Preprocess the sensor data uploaded by the sensor according to the gain coefficient and the offset;

[0167] A / D conversion module, used to perform digital-to-analog conversion on the pre-processed sensor data to obtain the environmental data corresponding to the sensor;

[0168] The data storage and transmission module is used to store and upload environmental data; the digital signal is stored by the data storage and transmission module and sent to the gateway controller at the same time. The data storage and transmission module is connected to the gateway controller through an interface to transmit the data to other parts of the system for further analysis and processing by the monitoring platform. In this process, the data storage and transmission module not only ensures the accurate storage of data, but also ensures the real-time transmission of data so as to respond to irrigation control decisions in a timely manner.

[0169] The sensor module mentioned above ensures the efficiency and accuracy of sensor data from collection to transmission. Through such signal processing and data transmission process, the system can obtain and process environmental data in real time, providing necessary support for automatic irrigation and remote monitoring.

[0170] Optionally, the visualization module is specifically used to:

[0171] Different fitting algorithms are adopted according to the complexity and linear relationship of environmental data;

[0172] According to the fitting algorithm, the environmental data is fitted to obtain the visual data;

[0173] Displays the data for visualization.

[0174] The visualization module is the core part of the real-time data display and analysis. It is divided into the sensor data visualization module and the irrigation data visualization module. The sensor data visualization module displays the environmental data obtained from each sensor in real time through charts, while the irrigation data visualization module displays and controls the irrigation parameters according to the irrigation control requirements.

[0175] Optional automatic irrigation module is specifically used for:

[0176] Set target environment data;

[0177] Set automatic irrigation frequency according to target environmental data;

[0178] Generate and execute automatic irrigation strategies based on target environmental data and target irrigation frequency.

[0179] The irrigation data visualization module is not only used to display sensor data in real time, but also enables precise control of the irrigation process through the settings and mode control modules. The module is designed to dynamically adjust irrigation parameters based on user needs and environmental monitoring data to ensure that plants receive the most suitable water.

[0180] In practical applications, in addition to multiple sensor modules, visualization modules, and automatic irrigation modules, the system also includes monitoring nodes, gateways, monitoring platforms, data servers, control centers, and user terminals; wherein the monitoring nodes monitor information on the irrigation environment and are connected to the gateway for wireless network communication; the monitoring nodes include sensor modules, which monitor the temperature, humidity, light intensity, and moisture content in the soil in the environment;

[0181] The gateway is connected to the monitoring platform through wireless network communication. The gateway is responsible for data transmission between the monitoring platform and the monitoring node, and controls the operation of the monitoring node according to the control command of the gateway controller in the monitoring node;

[0182] The monitoring platform is connected to the data server, and transmits the acquired data information to the data server for storage. The monitoring platform acquires the data in the monitoring node through the gateway, and further comprises a visualization module for performing visualization operations on the acquired data. The monitoring platform further comprises an automatic irrigation module for controlling the irrigation process of the plants to be irrigated according to the acquired data.

[0183] The data server stores data, and the data server also includes a data processing module, which converts the acquired data through an algorithm and sends it to the control center;

[0184] The control center establishes a local wireless communication connection with the user end and accepts its operation control, the control center controls the operation of the automatic irrigation module, the control center connects to the background management module in the monitoring platform, obtains relevant data query operations, and the control center receives data information transmitted by the data processing module;

[0185] The user terminal also accesses the data server through the control center to obtain historical data in the data server.

[0186] It should be noted that irrigation components and gateway controllers have been added to the monitoring nodes to form an intelligent irrigation system.

[0187] First, the irrigation component of the monitoring node consists of a water pump and a solenoid valve. The water pump is responsible for providing water to the plants that need irrigation, while the solenoid valve controls the switch of the water pump. The opening and closing of the solenoid valve determines whether the water pump works, thereby controlling the start and stop of irrigation. Specifically, the electrical connection between the solenoid valve and the water pump controls the working state of the irrigation system. Once the solenoid valve is opened, the water pump starts working and supplies water to the plants. When the solenoid valve is closed, the water pump stops working and irrigation ends. The gateway controller controls the solenoid valve through electrical signals to achieve precise irrigation.

[0188] At the same time, the gateway controller is also electrically connected to the wireless communication module to ensure that the monitoring node can transmit information to the gateway through the wireless network. The gateway is responsible for data communication between the monitoring platform and the monitoring node, so that the monitoring node can transmit the collected environmental data (such as temperature, humidity, light intensity and soil moisture content) to the monitoring platform in real time for further data analysis and processing.

[0189] Furthermore, in the system described in the embodiment of the present invention, the user end is connected to the cloud management platform through a mobile phone application to perform remote monitoring and control operations, and the monitoring platform supports the authority management of administrators and users through a background management module. The system also combines a camera for remote image monitoring to ensure the transparency and visualization of the irrigation process.

[0190] The user end (i.e. the user's mobile phone) can access the data server by logging into the cloud management platform. The data server includes a control module and a data storage module. The control module is further divided into a setting submodule and a feedback submodule. The setting submodule allows the user to send instructions to the control center through the mobile phone to perform automatic irrigation control or other operations. The feedback submodule is responsible for receiving feedback information from the control center and the data server and displaying it on the mobile phone interface, so that the user can understand the current irrigation status and system operation in real time.

[0191] The historical data storage in the data storage module caches the data calculated by the data processing module, including sensor data, irrigation control instructions and other information. These data will be stored regularly for subsequent query and analysis. The data transmitter is responsible for transmitting data from the monitoring platform to the server to ensure continuous data update and storage. Through the collaboration of these modules, users can query historical data and understand the long-term trend of plant irrigation.

[0192] To improve the visual management of the system, the monitoring node contains a camera that can remotely monitor the irrigation situation. The camera transmits real-time image data to the data storage and transmission module, and then transmits data through the gateway controller. Through the control center or the user end, the user can start the camera and make relevant settings. This allows the system to not only control the irrigation process, but also monitor the status of the plants in real time.

[0193] The plant automatic irrigation management method and system using the Internet of Things and remote monitoring provided by the embodiments of the present invention have at least the following effects in practical applications:

[0194] 1. The Internet of Things technology is used to realize real-time monitoring of the plant growth environment and automatically adjust the irrigation process. Through the real-time data obtained by the sensor module (such as temperature, humidity, light intensity and soil moisture, etc.), the system can accurately control the irrigation amount and timing to ensure the optimal humidity required for plant growth. In automatic irrigation mode, the system automatically adjusts the irrigation strategy according to the preset target humidity and irrigation frequency to avoid over-irrigation or under-irrigation, thereby saving water resources and improving irrigation efficiency. For example, if the soil humidity drops below the set value, the water pump and solenoid valve will automatically start irrigation until the humidity returns to the preset target.

[0195] 2. By integrating remote monitoring functions, users can view irrigation status and environmental data in real time through mobile phones or control centers, providing comprehensive plant management tools. Users can directly view sensor data, remotely start and stop irrigation processes, and even adjust irrigation frequency and humidity targets. At the same time, the camera integrated in the monitoring node allows users to monitor irrigation conditions in real time through images, thereby ensuring the transparency of the system and the accuracy of operations. Image information and data can be transmitted to the data server through the data storage module to ensure the real-time and reliability of the data.

[0196] 3. Through the data analysis and processing module, historical data and real-time collected information are combined to provide data support for irrigation decisions. Polynomial fitting, linear fitting and other data fitting algorithms are used to model and predict environmental parameters and irrigation data to help users adjust irrigation strategies more accurately. For example, through the linear fitting algorithm, the system can automatically adjust the irrigation frequency or water volume according to the trend of soil moisture changes to optimize the use of water resources and increase crop yields. The system's algorithm can also generate control instructions based on real-time data and preset conditions to ensure the efficiency and accuracy of the irrigation process.

[0197] 4. Through intelligent irrigation control, the system avoids unnecessary waste of water resources. When the soil moisture reaches the target value, the system will automatically stop irrigation to prevent over-irrigation and waste of water resources. The system combines the target humidity and frequency settings, and optimizes the irrigation process through data-driven control logic, which not only improves water resource utilization but also reduces energy consumption. Through real-time feedback from sensors and automated management of the control center, the system can dynamically adjust the irrigation frequency and timing according to the needs of the plants to ensure the optimal allocation of resources.

[0198] 5. The data of the monitoring node is transmitted to the monitoring platform through the wireless network, and then stored and calculated by the data server, ensuring the accuracy and real-time nature of the information. At the same time, the system's built-in cache mechanism ensures the temporary storage and recovery of data when the network is interrupted, ensuring the continuous operation of the system. For example, the sensor module stores the data after A / D conversion. In case the data cannot be transmitted immediately, the system will temporarily store the data in the register to ensure that the data will not be lost.

[0199] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present invention, which will not be described in detail here.

[0200] It should be noted that: the automatic irrigation management system for plants using the Internet of Things and remote monitoring provided in the above embodiments only uses the division of the above functional modules as an example when executing the automatic irrigation management method for plants using the Internet of Things and remote monitoring. In actual applications, the above functional distribution can be completed by different functional modules as needed, that is, the internal structure of the system is divided into different functional modules to complete all or part of the functions described above. In addition, the automatic irrigation management method for plants using the Internet of Things and remote monitoring and the system embodiments provided in the above embodiments belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0201] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0202] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for automatic plant irrigation management using the Internet of Things and remote monitoring, characterized in that: The method comprises: Through the Internet of Things, sensor data uploaded by multiple sensors are obtained; Preprocessing the sensor data to obtain environmental data; generating a visualization strategy and an automatic irrigation strategy according to the environmental data; The visualization strategy and the automatic irrigation strategy are executed.

2. The method according to claim 1, characterized in that The method further comprises: Preset multiple monitoring nodes; According to the monitoring requirements of the multiple monitoring nodes, corresponding multiple sensors are respectively set, and the multiple sensors are connected through the Internet of Things.

3. The method according to claim 2, characterized in that The preprocessing of the sensor data to obtain the environmental data comprises: Set the gain factor and offset corresponding to the sensor; Preprocessing the sensor data uploaded by the sensor according to the gain coefficient and the offset; The preprocessed sensor data is converted from digital to analog to obtain environmental data corresponding to the sensor.

4. The method according to claim 3, characterized in that Generating the visualization strategy according to the environmental data includes: According to the complexity and linear relationship of the environmental data, different fitting algorithms are adopted; According to the fitting algorithm, the environmental data is fitted to obtain visualization data; The visualization data is displayed.

5. The method according to claim 3, characterized in that: Generating the automatic irrigation strategy according to the environmental data includes: Set target environment data; According to the target environmental data, setting the automatic irrigation frequency; The automatic irrigation strategy is generated and executed according to the target environmental data and the target irrigation frequency.

6. The method according to claim 5, characterized in that After executing the automatic irrigation strategy, the method further includes: Obtain plant growth trend parameters; The target environmental data and the target irrigation frequency are corrected in real time according to the plant growth trend parameters.

7. A plant automatic irrigation management system using the Internet of Things and remote monitoring, characterized in that: The system includes multiple sensor modules, a visualization module, and an automatic irrigation module, wherein: The plurality of sensor modules are used for: Through the Internet of Things, sensor data uploaded by multiple sensors are obtained; Preprocessing the sensor data to obtain environmental data; The visualization module is used to generate a visualization strategy according to the environmental data and execute the visualization strategy; The automatic irrigation module is used to generate an automatic irrigation strategy according to the environmental data and execute the automatic irrigation strategy.

8. The system according to claim 7, characterized in that The sensor module specifically includes: Sensor, used to obtain sensor data; Signal conditioning modules for: Set the gain factor and offset corresponding to the sensor; Preprocessing the sensor data uploaded by the sensor according to the gain coefficient and the offset; An A / D conversion module is used to perform digital-to-analog conversion on the preprocessed sensor data to obtain environmental data corresponding to the sensor; The data storage and sending module is used to store and upload the environmental data.

9. The system according to claim 8, characterized in that: The visualization module is specifically used for: According to the complexity and linear relationship of the environmental data, different fitting algorithms are adopted; According to the fitting algorithm, the environmental data is fitted to obtain visualization data; The visualization data is displayed.

10. The system according to claim 8, characterized in that: The automatic irrigation module is specifically used for: Set target environment data; According to the target environmental data, setting the automatic irrigation frequency; The automatic irrigation strategy is generated and executed according to the target environmental data and the target irrigation frequency.

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