Accurate pesticide application real-time control method for agricultural plant protection unmanned aerial vehicle

Abstract

The invention discloses a real-time control method for precise pesticide application of an agricultural plant protection unmanned aerial vehicle, and the method comprises the following steps: 1, carrying out the boundary measurement of a land needing pesticide application based on an unmanned aerial vehicle measurement technology, and carrying out the data preprocessing of measurement data; 2, based on the Internet of Things technology, monitoring the meteorological data by using the Internet of Things technology, and importing the monitored meteorological data into a database for recording and storing; 3, in the pesticide application process of the plant protection unmanned aerial vehicle, combining the data monitored in the step 1 and the step 2 with pesticide application parameters; and 4, based on the parameter adjustment of the pesticide application operation of the plant protection unmanned aerial vehicle in the step 3, performing data recording on the parameter, and performing analysis and comparison on various data in the pesticide application process according to the agricultural growth condition so as to obtain a parameter adjustment method. Compared with the prior art, the device has the advantage that the conditions of spraying omission and re-spraying are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle control, and in particular to a real-time control method for precise pesticide application by an agricultural plant protection unmanned aerial vehicle. Background Art

[0002] Agricultural aviation plant protection technology is an important component of plant protection machinery. Compared with traditional manual application and ground mechanical application, plant protection drones do not need to contact the ground and can be used for spraying in hilly and mountainous areas where manual and ground machinery are difficult to reach. At the same time, due to its strong maneuverability, it can quickly transfer operations when facing large-scale insect pests, effectively reducing the losses caused by insect pests. The Chinese patent application number 202110792505.6 discloses a "real-time control method for precise pesticide application by a plant protection drone, comprising the following steps: (1) flight route planning; (2) dividing a farmland plot into multiple application areas; (3) controlling the plant protection drone to spray pesticides on the farmland. The pesticide application area is sprayed with pesticides. During the process of spraying the previous pesticide application area, the image of the next pesticide application area is collected, and the pest and disease degree information of the next pesticide application area is obtained after analysis and processing; (4) the control module calculates and obtains the flight spraying parameters of the next pesticide application area; (5) after the plant protection UAV flies into the next pesticide application area, the pesticide application operation is performed according to the flight spraying parameters, and the step (3) is returned to; (6) steps (3) to (5) are continuously repeated until the aerial spraying operation of the farmland is completed. The present invention enables the plant protection UAV to identify and analyze the farmland in real time and accurately spray pesticides, with high operation efficiency and accurate application amount.

[0003] This comparative document only solves the problem of precision pesticide spraying by drones in the existing technology. All of them first collect images of farmland plots and analyze pests and diseases. Only after obtaining the pesticide prescription map can normal drone aerial spraying work be carried out, which reduces the efficiency of aerial pesticide spraying of farmland, wastes time, and requires two drones to complete the above work, which consumes manpower and material resources and is cumbersome to operate. It does not take into account that during the spraying process, changes in external meteorological data will cause changes in the deposition position of pesticide droplets, making it impossible for pesticide droplets to be deposited in the target farmland area. In addition, during the pesticide application process, the pesticide may be sprayed out or the drone battery is too low and the spraying operation is not completed. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the above technical defects.

[0005] In order to solve the above problems, the technical solution of the present invention is: a real-time control method for precise pesticide application by an agricultural plant protection UAV, the control method comprising the following steps:

[0006] Step 1: Based on the drone measurement technology, the boundary of the land where the pesticide needs to be applied is measured, the measurement data is pre-processed, and the processed data is imported into the database for storage;

[0007] Step 2: Based on the Internet of Things technology, the Internet of Things technology is used to monitor the meteorological data, import the monitored meteorological data into the database for recording and storage, and use the monitored meteorological data for preliminary preprocessing to analyze the wind direction and precipitation in the area;

[0008] Step 3: During the pesticide application process of the plant protection drone, the flight pesticide application parameters of the plant protection drone are adjusted in real time based on the actual situation of the pesticide application area in the farmland, in combination with the monitoring data in steps 1 and 2 and the pesticide application parameters;

[0009] Step 4: Based on the parameter adjustment of the plant protection drone spraying operation in step 3, the parameters are recorded, and according to the agricultural growth conditions, various data in the spraying process are analyzed and compared to derive the parameter adjustment method.

[0010] Furthermore, based on the monitoring and storage of meteorological data in step 2, the monitored and stored data are sorted in descending order according to the storage time, and a time series curve graph of the corresponding category data is drawn according to the category of meteorological data in the database, so as to intuitively display the changes of the corresponding category data, and a wind speed and direction prediction model is constructed based on a recurrent neural network, including: (1) a wind speed and direction feature extraction layer, (2) a humidity feature extraction layer, (3) a temperature feature extraction layer, (4) a feature splicing layer, and (5) a wind speed and direction vector prediction layer. Based on the meteorological data collected when the plant protection UAV starts the spraying operation, the wind speed and direction data of the plant protection UAV during the spraying operation is predicted by the constructed wind speed and direction prediction model.

[0011] Furthermore, based on the intersection space formed by the straight-line propagation and curved refraction of light by the UAV measurement technology in step one, the terrain data is analyzed and the terrain coordinates are monitored through the payload equipment carried by the UAV, which includes GPS, inertial navigation system, camera, lidar and other technologies, and the measured data is recorded and transmitted in real time. The collected information is reviewed and analyzed through computer processing technology, and the characteristics of the terrain are mapped out using the restoration technology of the computer mapping system.

[0012] Furthermore, based on the process of the plant protection UAV performing the spraying operation in step three, the flight spraying parameters of the plant protection UAV are adjusted in real time based on the actual situation of the farmland spraying area. Specifically, the density of the plant protection UAV spraying is adjusted according to the actual agricultural planting situation, so that better spraying can be achieved.

[0013] The advantages of the present invention compared with the prior art are:

[0014] The present invention collects external meteorological data and establishes a corresponding wind speed and direction prediction model to plan the flight route of the plant protection UAV according to the predicted wind speed and direction and farmland pesticide application area information, and during the pesticide application operation of the plant protection UAV, the flight route of the plant protection UAV is fine-tuned based on the collected real-time wind speed and direction to ensure that the pesticide droplets can be deposited in the target farmland area, thereby achieving precise pesticide application in the farmland area, and at the same time, the flight endurance of the plant protection UAV is monitored in real time, and when the battery power of the plant protection UAV is lower than a preset threshold or the amount of pesticide carried by the plant protection UAV is sprayed, after the breakpoint position and longitude and latitude coordinates of the plant protection UAV are recorded, the plant protection UAV returns, and after the staff completes the processing, the plant protection UAV flies back to the recorded breakpoint position to continue pesticide spraying, thereby avoiding missed spraying and repeated spraying, and after the plant protection UAV completes the pesticide application operation, the actual spraying area layout map is obtained, thereby further avoiding missed spraying. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The present invention is a flow chart of a real-time control method for precise pesticide application by an agricultural plant protection UAV. DETAILED DESCRIPTION

[0016] The specific implementation of the present invention is further described below in conjunction with the accompanying drawings, wherein the same components are represented by the same reference numerals.

[0017] It should be noted that the words "front", "rear", "left", "right", "up" and "down" used in the following description refer to directions in the drawings, and the words "inside" and "outside" refer to directions toward or away from the geometric center of a specific component, respectively.

[0018] In order to make the contents of the present invention more clearly understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0019] like Figure 1 As shown, a real-time control method for precise pesticide application by an agricultural plant protection UAV is provided, and the control method comprises the following steps:

[0020] Step 1: Based on the drone measurement technology, the boundary of the land where the pesticide needs to be applied is measured, the measurement data is pre-processed, and the processed data is imported into the database for storage;

[0021] Step 2: Based on the Internet of Things technology, the Internet of Things technology is used to monitor the meteorological data, import the monitored meteorological data into the database for recording and storage, and use the monitored meteorological data for preliminary preprocessing to analyze the wind direction and precipitation in the area;

[0022] Step 3: During the pesticide application process of the plant protection drone, the flight pesticide application parameters of the plant protection drone are adjusted in real time based on the actual situation of the pesticide application area in the farmland, in combination with the monitoring data in steps 1 and 2 and the pesticide application parameters;

[0023] Step 4: Based on the parameter adjustment of the plant protection drone spraying operation in step 3, the parameters are recorded, and according to the agricultural growth conditions, various data in the spraying process are analyzed and compared to derive the parameter adjustment method.

[0024] Based on the monitoring and storage of meteorological data in step 2, the monitored and stored data are sorted in descending order according to the storage time, and a time series curve diagram of the corresponding category data is drawn according to the category of meteorological data in the database, so as to intuitively display the changes of the corresponding category data, and a wind speed and direction prediction model is constructed based on a recurrent neural network, including: (1) a wind speed and direction feature extraction layer, (2) a humidity feature extraction layer, (3) a temperature feature extraction layer, (4) a feature splicing layer, and (5) a wind speed and direction vector prediction layer. Based on the meteorological data collected when the plant protection UAV starts to apply pesticides, the wind speed and direction data of the plant protection UAV during the application of pesticides is predicted through the constructed wind speed and direction prediction model.

[0025] Based on the intersection space formed by the straight-line propagation and curved refraction of light by the UAV measurement technology in step one, the terrain data is analyzed and the terrain coordinates are monitored through the payload equipment carried by the UAV, which includes GPS, inertial navigation system, camera, lidar and other technologies, and the measured data is recorded and transmitted in real time. The collected information is reviewed and analyzed through computer processing technology, and the characteristics of the terrain are mapped out using the restoration technology of the computer mapping system.

[0026] Based on the process of the plant protection UAV applying pesticides in step three, the flight and spraying parameters of the plant protection UAV are adjusted in real time based on the actual situation of the farmland spraying area. Specifically, the density of the plant protection UAV spraying is adjusted according to the actual agricultural planting situation, so that better spraying can be achieved.

[0027] The present invention and its embodiments are described above, and such description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope of the present invention.

Claims

1. A real-time control method for precise pesticide application by an agricultural plant protection UAV, characterized in that: The control method comprises the following steps: Step 1: Based on the drone measurement technology, the boundary of the land where the pesticide needs to be applied is measured, the measurement data is pre-processed, and the processed data is imported into the database for storage; Step 2: Based on the Internet of Things technology, the Internet of Things technology is used to monitor the meteorological data, import the monitored meteorological data into the database for recording and storage, and use the monitored meteorological data for preliminary preprocessing to analyze the wind direction and precipitation in the area; Step 3: During the pesticide application process of the plant protection drone, the flight pesticide application parameters of the plant protection drone are adjusted in real time based on the actual situation of the pesticide application area in the farmland, in combination with the monitoring data in steps 1 and 2 and the pesticide application parameters; Step 4: Based on the parameter adjustment of the plant protection drone spraying operation in step 3, the parameters are recorded, and according to the agricultural growth conditions, various data in the spraying process are analyzed and compared to derive the parameter adjustment method.

2. The method for real-time control of precise pesticide application by an agricultural plant protection UAV according to claim 1, characterized in that: Based on the monitoring and storage of meteorological data in step 2, the monitored and stored data are sorted in descending order according to the storage time, and a time series curve diagram of the corresponding category data is drawn according to the category of meteorological data in the database, so as to intuitively display the changes of the corresponding category data, and a wind speed and direction prediction model is constructed based on a recurrent neural network, including: (1) a wind speed and direction feature extraction layer, (2) a humidity feature extraction layer, (3) a temperature feature extraction layer, (4) a feature splicing layer, and (5) a wind speed and direction vector prediction layer. Based on the meteorological data collected when the plant protection UAV starts to apply pesticides, the wind speed and direction data of the plant protection UAV during the application of pesticides is predicted through the constructed wind speed and direction prediction model.

3. The method for real-time control of precise pesticide application by an agricultural plant protection UAV according to claim 1, characterized in that: Based on the intersection space formed by the straight-line propagation and curved refraction of light by the UAV measurement technology in step one, the terrain data is analyzed and the terrain coordinates are monitored through the payload equipment carried by the UAV, which includes GPS, inertial navigation system, camera, lidar and other technologies, and the measured data is recorded and transmitted in real time. The collected information is reviewed and analyzed through computer processing technology, and the characteristics of the terrain are mapped out using the restoration technology of the computer mapping system.

4. The method for real-time control of precise pesticide application by an agricultural plant protection UAV according to claim 1, characterized in that: Based on the process of the plant protection UAV applying pesticides in step three, the flight and spraying parameters of the plant protection UAV are adjusted in real time based on the actual situation of the farmland spraying area. Specifically, the density of the plant protection UAV spraying is adjusted according to the actual agricultural planting situation, so that better spraying can be achieved.

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