Intelligent agricultural irrigation system based on Internet of Things

Abstract

The invention discloses an intelligent agricultural irrigation system based on Internet of Things, which comprises an information collection module, an irrigation analysis module and an irrigation management module, and is characterized in that the information collection module is used for collecting and obtaining related information of an irrigation area, and the irrigation analysis module is used for analyzing and calculating the appropriate irrigation water amount of the current irrigation area; the irrigation management module is used for controlling the real-time irrigation condition of an irrigation area, the information collection module is electrically connected with the irrigation analysis module, and the irrigation analysis module is electrically connected with the irrigation management module. Timely water supply is ensured; and water waste is avoided. Therefore, the problem that the yield of crops is reduced due to the fact that water supply is difficult to guarantee evenly in a traditional irrigation mode is solved, the utilization efficiency of agricultural water resources is improved, intelligent and efficient agricultural irrigation management is achieved, and the system has the advantages of being intelligent and refined.

Description

Technical Field

[0001] This invention relates to the field of agricultural irrigation technology, specifically to an intelligent agricultural irrigation system based on the Internet of Things. Background Technology

[0002] Traditional agricultural irrigation methods primarily employ timed and quantitative irrigation, but these are constrained by factors such as weather and terrain slope, making it difficult to achieve uniform and timely water supply to crops. This leads to a series of problems, such as reduced crop yields, crop curling, and poor fertilizer absorption. Furthermore, soils with varying degrees of compaction require different irrigation volumes, and for deep-rooted crops, irrigation water needs to fully penetrate the root system. However, traditional irrigation methods easily lead to soil compaction, with water remaining on the surface and being lost or evaporated, resulting in insufficient actual irrigation water and inadequate penetration. There is an urgent need for a new intelligent agricultural irrigation system and method to overcome the limitations of traditional irrigation methods. Therefore, designing intelligent and precise IoT-based intelligent agricultural irrigation systems and methods is essential. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent agricultural irrigation system and method based on the Internet of Things (IoT) to solve the problems mentioned in the background art.

[0004] To address the aforementioned technical problems, this invention provides the following technical solution: an intelligent agricultural irrigation system and method based on the Internet of Things, comprising an information collection module, an irrigation analysis module, and an irrigation management module, characterized in that: the information collection module is used to collect relevant information about the irrigation area; the irrigation analysis module is used to analyze and calculate the appropriate irrigation water volume for the current irrigation area; the irrigation management module is used to control the real-time irrigation status of the irrigation area; the information collection module is electrically connected to the irrigation analysis module; and the irrigation analysis module is electrically connected to the irrigation management module.

[0005] According to the above technical solution, the information collection module includes an irrigation information database, a soil acquisition module, a growth monitoring module, and a weather forecasting module. The irrigation information database is used to store the irrigation data required by the irrigated crops and the basic information of the crops. The soil acquisition module is used to capture and collect soil image information of the irrigated area through a camera module. The growth monitoring module is used to detect the growth of crops through radar. The weather forecasting module is used to obtain weather forecast information of the irrigated area.

[0006] According to the above technical solution, the irrigation analysis module includes a soil compaction degree analysis module, an irrigation water flow analysis module, and an irrigation volume calculation module. The soil compaction degree analysis module is used to analyze and determine the soil compaction degree information of the irrigation area. The irrigation water flow analysis module is used to analyze and calculate the maximum irrigation water flow of the current irrigation area. The irrigation volume calculation module is used to analyze and calculate the irrigation water volume based on the soil compaction degree, irrigation water flow, and weather conditions.

[0007] According to the above technical solution, the irrigation management module includes a soil loosening prompt unit, an irrigation water flow control module, and an irrigation water volume management module. The soil loosening prompt unit is used to determine and prompt whether the irrigated soil needs to be loosened. The irrigation water flow control module is used to control the irrigation water flow in real time based on the analysis results. The irrigation water volume management module is used to manage and control the total amount of water used for a single irrigation by the irrigation equipment.

[0008] A smart agricultural irrigation method based on the Internet of Things (IoT) includes the following steps: Step S1: Establish an irrigation information database to register and store crop information in the irrigated area, including crop types, planting time, and irrigation water requirements; Step S2: Use the soil acquisition module to access the camera module and acquire soil images of the irrigation area; Step S3: In agricultural irrigation areas, monitor the growth of crops using a growth monitoring module; Step S4: Obtain local weather and precipitation information via the internet; Step S5: Analyze the soil compaction degree based on the soil images obtained by the soil acquisition module; Step S6: Analyze and calculate the maximum irrigation flow rate based on the soil compaction degree and the current irrigated crop information; Step S7: Next, calculate the irrigation water volume based on the irrigation water flow rate and weather conditions; Step S8: Finally, the system updates the irrigation analysis results in real time and manages and controls the irrigation process.

[0009] According to the above technical solution, the method for monitoring crop growth in step S3 is as follows: Step S31: Set up a growth monitoring point directly above the crop being monitored; Step S32: The growth monitoring module triggers a signal to control the signal transmitting unit at the growth monitoring point to transmit radar signals; Step S33: When the crop reaches its peak, a signal is fed back. The growth monitoring module obtains the distance l from the monitoring point to the crop peak based on the signal attenuation and the preset distance conversion coefficient. Step S34: Based on the height H and distance l of the monitoring point, use the formula... The height h of the crop is calculated. Step S35: The growth monitoring module outputs the growth signal of the crop at the crop height h.

[0010] According to the above technical solution, step S5 further includes the following steps: Step S51: Obtain soil images taken at an oblique angle, identify the boundary contour between the soil surface and the background from the cross section, and enlarge the image proportionally; Step S52: Fit a contour line to the surface features of the boundary contour; Step S53: Select the starting point and ending point of the contour line and connect them with line segment L. Establish a plane rectangular coordinate system with the starting point of the contour line as the origin, the line containing line segment L as the X-axis, and the line perpendicular to line segment L and passing through the origin as the Y-axis. Step S54: Place the contour line on the coordinate system by aligning the start and end points of the contour line with the start and end points of line segment L; Step S55: Mark the points on the contour line at a fixed distance c on the X-axis, and obtain the point coordinates on the Y-axis as b. ; Step S56: Using the formula Calculate the soil compaction value B, where k is the conversion coefficient between the fluctuation of the data on the contour line and the soil surface compaction of the current irrigated area, and is a constant greater than 0.

[0011] According to the above technical solution, step S6 further includes the following steps: Step S61: Obtain the soil compaction degree value B of the irrigated area; Step S62: Based on the irrigation information database, obtain the type and planting time of the currently irrigated crop, retrieve the normal growth range value of the crop from the irrigation information database according to the planting time of the crop, and then make a judgment based on the crop height h output by the growth monitoring module. Step S63: If the growth is not within the normal growth range, the system will issue an abnormal growth warning and switch the subsequent irrigation management authority to manual setting management; if the growth is within the normal growth range, the system will continue to retrieve the rooting depth value r of the crop under the current growth condition from the irrigation information database. Step S64: Using the formula: The maximum irrigation flow rate U is calculated, where... These are control parameters.

[0012] According to the above technical solution, step S7 further includes the following steps: Step S71: Retrieve the ideal irrigation water requirement q based on the current growth status of the irrigated crop from the irrigation information database; Step S72: The formula for calculating irrigation water volume is: In the formula, is the conversion coefficient between irrigation flow rate and irrigation volume, is a constant greater than 0, j is the rainfall value during the predicted irrigation cycle, and Q is the actual required irrigation volume.

[0013] According to the above technical solution, step S8 further includes: Step S81: When the soil compaction degree B is greater than the maximum compaction degree requirement of the irrigated crop under the current growth status in the irrigation information database, the soil loosening prompt unit triggers the output of a soil loosening prompt signal; Step S82: When the irrigation time is reached, the system analyzes and outputs the results from the irrigation analysis module, and controls the irrigation of crops in real time with irrigation water flow rate U and irrigation water volume Q.

[0014] Compared with existing technologies, the beneficial effects achieved by this invention are as follows: This invention achieves refined control of the irrigation process through the collaborative operation of information collection, irrigation analysis, and irrigation management modules. Simultaneously, it can dynamically calculate the optimal irrigation water volume based on factors such as soil compaction and crop growth status, ensuring timely water supply and avoiding water waste. This solves the problems of traditional irrigation methods, such as the difficulty in uniformly guaranteeing water supply and resulting in reduced crop yields, thereby improving agricultural water resource utilization efficiency and realizing intelligent and efficient agricultural irrigation management. Attached Figure Description

[0015] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the system module composition of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1The present invention provides a technical solution: an intelligent agricultural irrigation system based on the Internet of Things, comprising an information collection module, an irrigation analysis module, and an irrigation management module. The information collection module is used to collect relevant information about the irrigation area, the irrigation analysis module is used to analyze and calculate the appropriate irrigation water volume for the current irrigation area, and the irrigation management module is used to control the real-time irrigation status of the irrigation area. The information collection module is electrically connected to the irrigation analysis module, and the irrigation analysis module is electrically connected to the irrigation management module.

[0018] The information collection module includes an irrigation information database, a soil acquisition module, a growth monitoring module, and a weather forecasting module. The irrigation information database is used to store the irrigation data required by the irrigated crops and the basic information of the crops. The soil acquisition module is used to capture and collect soil images of the irrigated area through a camera module. The growth monitoring module is used to detect the growth of crops through radar. The weather forecasting module is used to obtain weather forecast information for the irrigated area.

[0019] The irrigation analysis module includes a soil compaction analysis module, an irrigation water flow analysis module, and an irrigation volume calculation module. The soil compaction analysis module is used to analyze and determine the soil compaction information of the irrigation area. The irrigation water flow analysis module is used to analyze and calculate the maximum irrigation water flow of the current irrigation area. The irrigation volume calculation module is used to analyze and calculate the irrigation volume based on the soil compaction, irrigation water flow, and weather conditions.

[0020] The irrigation management module includes a soil loosening prompt unit, an irrigation water flow control module, and an irrigation water volume management module. The soil loosening prompt unit is used to determine and prompt when the irrigated soil needs to be loosened. The irrigation water flow control module is used to control the irrigation water flow in real time based on the analysis results. The irrigation water volume management module is used to manage and control the total amount of water used by the irrigation equipment in a single irrigation.

[0021] A smart agricultural irrigation method based on the Internet of Things (IoT) includes the following steps: Step S1: Establish an irrigation information database to register and store crop information in the irrigated area, including crop types, planting time, and irrigation water requirements; Step S2: Use the soil acquisition module to access the camera module and acquire soil images of the irrigation area; Step S3: In agricultural irrigation areas, monitor the growth of crops using a growth monitoring module; Step S4: Obtain local weather and precipitation information via the internet; Step S5: Analyze the soil compaction degree based on the soil images obtained by the soil acquisition module; Step S6: Analyze and calculate the maximum irrigation flow rate based on the soil compaction degree and the current irrigated crop information; Step S7: Next, calculate the irrigation water volume based on the irrigation water flow rate and weather conditions; Step S8: Finally, the system updates the irrigation analysis results in real time and manages and controls the irrigation process.

[0022] In step S3, the method for monitoring crop growth is as follows: Step S31: Set up a growth monitoring point directly above the crop being monitored; Step S32: The growth monitoring module triggers a signal to control the signal transmitting unit at the growth monitoring point to transmit radar signals; Step S33: When the crop reaches its peak, a signal is fed back. The growth monitoring module obtains the distance l from the monitoring point to the crop peak based on the signal attenuation and the preset distance conversion coefficient. Step S34: Based on the height H and distance l of the monitoring point, use the formula... The height h of the crop is calculated. Step S35: The growth monitoring module outputs the growth signal of the crop at the crop height h.

[0023] Step S5 further includes the following steps: Step S51: Obtain soil images taken at an oblique angle, identify the boundary contour between the soil surface and the background from the cross section, and enlarge the image proportionally; Step S52: Fit a contour line to the surface features of the boundary contour; Step S53: Select the starting point and ending point of the contour line and connect them with line segment L. Establish a plane rectangular coordinate system with the starting point of the contour line as the origin, the line containing line segment L as the X-axis, and the line perpendicular to line segment L and passing through the origin as the Y-axis. Step S54: Place the contour line on the coordinate system by aligning the start and end points of the contour line with the start and end points of line segment L; Step S55: Mark the points on the contour line at a fixed distance c on the X-axis, and obtain the point coordinates on the Y-axis as b. ; Step S56: Using the formula The soil compaction degree value B is calculated, where k is the conversion coefficient between the fluctuation of the calibration data on the contour line and the soil surface compaction degree of the current irrigation area, which is a constant greater than 0. The greater the distance between the calibration point and the X-axis, the greater the dispersion of the calibration point, indicating that the soil surface is more rugged and relatively loose. Conversely, the smaller the distance between the calibration point and the X-axis, the smaller the dispersion of the calibration point, indicating that the soil surface is flatter and the soil is more compacted. Therefore, the compaction degree value B is larger.

[0024] Step S6 further includes the following steps: Step S61: Obtain the soil compaction degree value B of the irrigated area; Step S62: Based on the irrigation information database, obtain the type and planting time of the currently irrigated crop, retrieve the normal growth range value of the crop from the irrigation information database according to the planting time of the crop, and then make a judgment based on the crop height h output by the growth monitoring module. Step S63: If the growth is not within the normal growth range, the system will issue an abnormal growth warning and switch the subsequent irrigation management authority to manual setting management; if the growth is within the normal growth range, the system will continue to retrieve the rooting depth value r of the crop under the current growth condition from the irrigation information database. Step S64: Using the formula: The maximum irrigation flow rate U is calculated, where... To control the parameters, the formula shows that the maximum irrigation flow rate U is inversely proportional to both soil compaction and crop root depth. More compacted the soil, the harder it is for the irrigation water to be absorbed, leading to more water remaining on the soil surface and being lost, resulting in insufficient irrigation. Increasing the irrigation volume would also waste water resources. Similarly, deeper plant roots require longer soil moisture intake to fully penetrate the soil and reach all the crop roots. To further prevent waterlogging caused by rapid irrigation flow, the root depth parameter in the formula allows for precise control of irrigation water volume based on crop root depth, ensuring effective irrigation while avoiding waterlogging.

[0025] Step S7 further includes the following steps: Step S71: Retrieve the ideal irrigation water requirement q based on the current growth status of the irrigated crop from the irrigation information database; Step S72: The formula for calculating irrigation water volume is: In the formula, is the conversion coefficient between irrigation flow rate and irrigation volume, is a constant greater than 0, j is the rainfall value during the predicted irrigation cycle, and Q is the actual required irrigation volume.

[0026] Step S8 further includes: Step S81: When the soil compaction degree B is greater than the maximum compaction degree requirement of the irrigated crop under the current growth status in the irrigation information database, the soil loosening prompt unit triggers the output of a soil loosening prompt signal; Step S82: When the irrigation time is reached, the system analyzes the output results from the irrigation analysis module and controls the irrigation of crops in real time with irrigation flow rate U and irrigation volume Q. Through the collaborative operation of the information collection, irrigation analysis, and irrigation management modules, refined control of the irrigation process is achieved. Simultaneously, the system can dynamically calculate the optimal irrigation volume based on factors such as soil compaction and crop growth status, ensuring timely water supply and avoiding water waste. This solves the problems of traditional irrigation methods, such as difficulty in uniformly guaranteeing water supply and resulting in reduced crop yields, improves agricultural water resource utilization efficiency, and achieves intelligent and efficient agricultural irrigation management.

[0027] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0028] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An Internet of Things-based intelligent agricultural irrigation system, comprising an information collection module, an irrigation analysis module, and an irrigation management module, characterized in that: The information collection module is used to collect relevant information about the irrigation area, the irrigation analysis module is used to analyze and calculate the appropriate irrigation water volume for the current irrigation area, and the irrigation management module is used to control the real-time irrigation situation of the irrigation area. The information collection module is electrically connected to the irrigation analysis module, and the irrigation analysis module is electrically connected to the irrigation management module. The information collection module includes an irrigation information database, a soil acquisition module, a growth monitoring module, and a weather forecasting module. The irrigation information database is used to store irrigation data required by the irrigated crops and basic information about the crops. The soil acquisition module is used to capture and collect soil images of the irrigated area using a camera module. The growth monitoring module is used to detect the growth of the crops using radar. The weather forecasting module is used to obtain weather forecast information for the irrigated area. The irrigation analysis module includes a soil compaction analysis module, an irrigation water flow analysis module, and an irrigation volume calculation module. The soil compaction analysis module is used to analyze and determine the soil compaction information of the irrigation area. The irrigation water flow analysis module is used to analyze and calculate the maximum irrigation water flow of the current irrigation area. The irrigation volume calculation module is used to analyze and calculate the irrigation volume based on the soil compaction, irrigation water flow, and weather conditions. The irrigation management module includes a soil loosening prompt unit, an irrigation water flow control module, and an irrigation water volume management module. The soil loosening prompt unit is used to determine and prompt whether the irrigated soil needs to be loosened. The irrigation water flow control module is used to control the irrigation water flow in real time based on the analysis results. The irrigation water volume management module is used to manage and control the total amount of water used by the irrigation equipment in a single irrigation.

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