An information monitoring system based on rural internet of things

Abstract

The application discloses an information monitoring system based on rural internet of things, which comprises a general control device, monitoring platforms and unmanned aerial vehicles, the monitoring platforms are multiple, the general control device is connected to the monitoring platforms, the monitoring platforms are connected to the unmanned aerial vehicles, the general control device comprises a single-chip microcomputer, a power module, a storage module, a man-machine interaction module and a communication module, the power module, the storage module, the man-machine interaction module and the communication module are all connected to the single-chip microcomputer, and the monitoring platform comprises a microprocessor, sensors, a power module and an unmanned aerial vehicle platform. The application has the beneficial effects that: the monitoring platforms are arranged in the monitoring area, the crop information is monitored through the sensors on the monitoring platforms, when an abnormality occurs, the unmanned aerial vehicle enters the monitoring platform coverage area for deep monitoring, so that more accurate data can be obtained; the unmanned aerial vehicle platform is provided with a charging module, the unmanned aerial vehicle can be charged on the platform, and long-time monitoring is realized; full-automatic operation can be realized, and a large amount of labor cost can be saved.

Description

Technical Field

[0001] This invention relates to an information monitoring system based on the Internet of Things in rural areas, belonging to the field of information monitoring technology. Background Technology

[0002] Crop information monitoring utilizes advanced technologies and tools to collect, analyze, and monitor various data in farmland in order to improve agricultural production efficiency, reduce resource waste, and ensure crop health and yield.

[0003] Chinese invention patent CN113325868B discloses a "Real-time Crop Identification System and Method Based on Unmanned Aerial Vehicles (UAVs)," comprising a UAV platform, a flight path planning module, a crop identification module, a server, and a mobile terminal. The UAV platform includes an image acquisition device and a crop identification module, while the flight path planning module is located within the server. The invention also discloses a real-time crop identification method based on UAVs. This method involves planning the UAV flight path on the server and uploading it to the mobile terminal. Upon receiving instructions, the UAV can perform crop image acquisition and real-time crop identification tasks, uploading the obtained crop images and the final identification results to an agricultural information database. The crop type identification module is implemented based on a crop identification model trained with YOLOv3. However, when conducting large-area information monitoring, the UAV needs frequent takeoffs and landings, and the monitoring is indiscriminate across the entire area, requiring improvements in the targeting and efficiency of the monitoring. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an information monitoring system based on the Internet of Things in rural areas. This monitoring system deploys a monitoring platform in the monitoring area to monitor crop information. When abnormal data is detected, a drone enters the coverage area of ​​the monitoring platform to conduct in-depth monitoring and obtain more accurate data.

[0005] This invention is achieved through the following scheme: an information monitoring system based on rural Internet of Things, comprising a central control device, a monitoring platform, and a drone. Multiple monitoring platforms are included, with the central control device connected to each monitoring platform and the monitoring platform connected to the drone. The central control device includes a microcontroller, a power module, a storage module, a human-machine interaction module, and a communication module. The power module, storage module, human-machine interaction module, and communication module are all connected to the microcontroller. The monitoring platform includes a microprocessor, sensors, a power module, and a drone platform.

[0006] The sensors include a meteorological sensor, a carbon dioxide sensor, a soil pH sensor, a biosensor, a soil moisture sensor, a soil temperature sensor, a soil conductivity sensor, and a light sensor. The microprocessor is connected to the sensors via a UART serial port.

[0007] The microcontroller is connected to the storage module and the communication module via UART serial port communication.

[0008] The unmanned aerial vehicle platform is connected to the microprocessor via RS232 communication.

[0009] The drone platform has a charging module and a data transmission module. The drone can be parked on the drone platform. The drone is connected to the charging module. The drone and the monitoring platform transmit data through the data transmission module.

[0010] The drone includes a body, wings connected to the four corners of the body, a battery connected to the upper part of the body, a support frame connected to the lower part of the body, a data collection mechanism connected to the center of the lower part of the body, high-resolution cameras connected around the data collection mechanism, and a sonar sensor and a multispectral sensor connected to the lower part of the data collection mechanism.

[0011] There are six high-resolution cameras.

[0012] There are two supports, and the data collection mechanism is located between the two supports.

[0013] There are two batteries, and the batteries are replaceable.

[0014] The monitoring platform collects monitoring data through the sensors and calculates and predicts growth trends using a microprocessor. The steps are as follows: S1. Obtain information on multiple time periods in the historical data of the monitoring area, including meteorological information, carbon dioxide information, soil pH information, soil moisture information, soil temperature information, soil conductivity information, and light information; S2. Analyze the growth status of crops, provide a predicted growth status curve, and generate a crop growth prediction vector map. S3. The high-resolution camera of the UAV takes pictures of crops in the area, and combines the sonar sensor and multispectral sensor to obtain a vector map of the target crops based on the spectral features of the high-resolution remote sensing image. S4. Compare the vector map of the spectral features of the target crops based on high-resolution remote sensing images with the crop growth prediction vector map, and determine the regional monitoring frequency based on the degree of agreement.

[0015] The beneficial effects of this invention are as follows: 1. The present invention provides an information monitoring system based on the Internet of Things in rural areas. By deploying a monitoring platform in the monitoring area, the system monitors crop information through sensors on the monitoring platform. When abnormal data is detected, a drone enters the coverage area of ​​the monitoring platform to conduct in-depth monitoring, take high-definition pictures, and intelligently identify the abnormal data, thereby obtaining more accurate data and making more accurate judgments on the crops. 2. The drone platform of the information monitoring system based on rural Internet of Things of the present invention has a charging module, and the drone can be charged on the drone platform to achieve long-term monitoring; 3. The information monitoring system based on the Internet of Things in rural areas of this invention can achieve fully automated operation, saving a lot of labor costs; 4. In order to reduce the number of drones and conduct differentiated monitoring in different areas, the present invention provides an information monitoring system based on the Internet of Things in rural areas. By comparing the predicted growth trend obtained by the monitoring platform with the actual growth calculated by the drone footage, the monitoring frequency of drone footage in each area is determined, and differentiated monitoring is implemented. More frequent monitoring is carried out in key areas, which saves monitoring resources and reduces the cost of use. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the system framework of an embodiment of the information monitoring system based on the Internet of Things in rural areas according to the present invention.

[0017] Figure 2 This is a schematic diagram of the overall control device framework of an embodiment of the information monitoring system based on rural Internet of Things of the present invention.

[0018] Figure 3 This is a schematic diagram of the monitoring platform framework of an embodiment of the information monitoring system based on rural Internet of Things of the present invention.

[0019] Figure 4 This is a front view schematic diagram of an unmanned aerial vehicle (UAV) according to a first embodiment of an information monitoring system based on rural Internet of Things (IoT) of the present invention.

[0020] Figure 5 This is a flowchart illustrating a second embodiment of the information monitoring system based on the Internet of Things in rural areas according to the present invention.

[0021] In the diagram: 1 is the fuselage, 2 is the wing, 3 is the support frame, 4 is the battery, 5 is the data collection mechanism, 6 is the high-resolution camera, 7 is the sonar sensor, and 8 is the multispectral sensor. Detailed Implementation

[0022] The following is combined with Figures 1-4 The present invention will be further described, but the scope of protection of the present invention is not limited to the contents described herein.

[0023] Identical components are represented by the same reference numerals. It should be noted that the terms "front," "rear," "left," "right," "up," and "down" used in the following description refer to directions in the accompanying drawings, while the terms "inner" and "outer" refer to directions toward or away from the geometric center of a specific component, respectively. Furthermore, the accompanying drawings are all in a very simplified form and use non-precise ratios, and are only used to facilitate and clearly illustrate the purpose of the embodiments of the present invention.

[0024] For clarity, not all features of the actual embodiments will be described. In the following description, well-known functions and structures will not be described in detail, as they would confuse the invention with unnecessary details. It should be understood that in the development of any actual embodiment, a great deal of implementation detail must be made to achieve the developer’s specific goals, such as changing one embodiment to another according to the limitations of the system or business. In addition, it should be understood that such development work may be complex and time-consuming, but is merely routine work for those skilled in the art.

[0025] Example 1

[0026] Reference Figure 1-3 An information monitoring system based on the Internet of Things in rural areas includes a central control device, a monitoring platform, and drones. There are multiple monitoring platforms. The central control device is connected to the monitoring platform, and the monitoring platform is connected to the drone. The central control device includes a microcontroller, a power module, a storage module, a human-machine interaction module, and a communication module. The power module, storage module, human-machine interaction module, and communication module are all connected to the microcontroller. The monitoring platform includes a microprocessor, sensors, a power module, and a drone platform.

[0027] The sensors include meteorological sensors, carbon dioxide sensors, soil pH sensors, biological sensors, soil moisture sensors, soil temperature sensors, soil conductivity sensors, and light sensors. The microprocessor communicates with the sensors via a UART serial port.

[0028] The microcontroller is an STM32F407, and it is connected to the storage module and communication module via UART serial port.

[0029] The drone platform and the microprocessor are connected via RS232 communication.

[0030] The drone platform has a charging module and a data transmission module. The drone can be parked on the drone platform, connected to the charging module, and the drone transmits data to the monitoring platform through the data transmission module.

[0031] Reference Figure 4The drone includes a body 1, wings 2 connected to the four corners of the body 1, a battery 4 connected to the upper part of the body 1, a support 3 connected to the lower part of the body 1, a data collection mechanism 5 connected to the lower center of the body 1, high-resolution cameras 6 connected around the data collection mechanism 5, and a sonar sensor 7 and a multispectral sensor 8 connected to the lower part of the data collection mechanism 5.

[0032] The high-resolution camera 6 has the following specifications: Sony Alpha 7R IV, resolution: 61 MP, sensor: 35.9 x 24mm Exmor R CMOS. There are six high-resolution cameras 6, two brackets 3, a data collection mechanism 5 between the two brackets 3, and two batteries 4. The batteries 4 are replaceable.

[0033] During system operation, sensors on the monitoring platform monitor relevant data and transmit the information to the central control unit, specifically: Meteorological sensors: used to monitor and measure various meteorological parameters in the atmosphere, including temperature, humidity, air pressure, wind speed, and wind direction; Carbon dioxide sensor: Used to measure the concentration of carbon dioxide in the environment, model Senseair S8, with a UART output interface; Soil pH sensor: Used to measure the acidity and alkalinity of soil, specification: SparkFun Soil pH Sensor, measurement range: 3.5 to 9; Soil moisture sensor: used to measure the moisture content in soil; Soil temperature sensor: The soil temperature sensor is used to measure the temperature of the soil. It is an NTC thermistor sensor with an output interface of Analog. Soil conductivity sensor: Used to measure soil conductivity and electrolyte content, which is of great significance for monitoring soil salinity, water content, etc. The EC-5 soil conductivity sensor is used, ranging from 0.3 dS / m to 10 dS / m, with an output interface of Analog.

[0034] When the sensors on the monitoring platform detect abnormal data, the data is transmitted to the central control unit. The central control unit then sends instructions to the drone, which flies to the area of ​​abnormal data for in-depth monitoring. Further data monitoring is conducted using high-resolution cameras, sonar sensors, and multispectral sensors.

[0035] During flight, the drone can automatically enter the drone platform on the monitoring platform for charging.

[0036] Example 2

[0037] Reference Figure 5To reduce the number of drones and conduct differentiated monitoring in different areas, the monitoring platform compares the predicted growth trends with the actual growth calculated from drone footage to determine the drone monitoring frequency for each area. This differentiated monitoring, with higher frequency monitoring for key areas, conserves monitoring resources and reduces operating costs. The monitoring platform collects monitoring data through sensors and uses a microprocessor to calculate and predict growth trends. The steps are as follows: S1. Obtain information on multiple time periods in the historical data of the monitoring area, including meteorological information, carbon dioxide information, soil pH information, soil moisture information, soil temperature information, soil conductivity information, and light information; S2. Analyze the growth status of crops, provide a predicted growth status curve, and generate a crop growth prediction vector map. S3. The high-resolution camera of the drone takes pictures of crops in the area, and combined with sonar and multispectral sensors, it obtains a vector map of the target crops based on the spectral features of the high-resolution remote sensing images. S4. Compare the vector map of the spectral features of the target crops based on high-resolution remote sensing images with the crop growth prediction vector map, and determine the regional monitoring frequency based on the degree of agreement.

[0038] In step S4, if the vector map of the target crop based on the spectral features of the high-resolution remote sensing image and the crop growth prediction vector map have a matching degree of more than 90%, then it is determined to be a low-frequency monitoring area. If the vector map of the target crop based on the spectral characteristics of high-resolution remote sensing image meets the crop growth prediction vector map with a degree of conformity of 60%-90%, then it is identified as a medium-frequency monitoring area. If the vector map of the target crop based on the spectral characteristics of high-resolution remote sensing imagery matches the crop growth prediction vector map with a degree of agreement of less than 60%, then it is identified as a high-frequency monitoring area. Although the technical solutions of the present invention have been described and enumerated in detail, it should be understood that modifications to the above embodiments or the adoption of equivalent alternatives are obvious to those skilled in the art. Such modifications or improvements made without departing from the spirit of the present invention are all within the scope of protection claimed by the present invention.

Claims

1. An information monitoring system based on the Internet of Things in rural areas, characterized in that, It includes a central control unit, a monitoring platform, and drones. Multiple monitoring platforms are included, with the central control unit connected to each platform and the monitoring platforms connected to the drones. The central control unit includes a microcontroller, a power module, a storage module, a human-machine interface module, and a communication module. The power module, storage module, human-machine interface module, and communication module are all connected to the microcontroller. The monitoring platform includes a microprocessor, sensors, a power module, and a drone platform. The sensors include a meteorological sensor, a carbon dioxide sensor, a soil pH sensor, a biosensor, a soil moisture sensor, a soil temperature sensor, a soil conductivity sensor, and a light sensor. The microprocessor communicates with the sensors via a UART serial port. The drone platform has a charging module and a data transmission module, and the drone can be parked on the drone platform. The human-machine interface is connected to the charging module, and the drone and the monitoring platform transmit data through the data transmission module. The drone includes a body (1), wings (2) are connected to the four corners of the body (1), a battery (4) is connected to the upper part of the body (1), a bracket (3) is connected to the lower part of the body (1), a data collection mechanism (5) is connected to the lower center of the body (1), a high-resolution camera (6) is connected around the data collection mechanism (5), and a sonar sensor (7) and a multispectral sensor (8) are connected to the lower part of the data collection mechanism (5). When the sensors of the monitoring platform detect abnormal data, the data is transmitted to the central control device, the central control device sends instructions to the drone, the drone flies to the abnormal data area, performs in-depth monitoring, and further data monitoring is carried out through the high-resolution camera (6), the sonar sensor (7) and the multispectral sensor (8). The monitoring platform collects monitoring data through the sensors and calculates and predicts growth trends using a microprocessor. The steps are as follows: S1. Obtain information on multiple time periods in the historical years of the monitoring area, including meteorological information, carbon dioxide information, soil pH information, soil moisture information, soil temperature information, soil conductivity information, and light information; S2. Analyze the growth status of crops, provide a predicted growth status curve, and generate a crop growth prediction vector map. S3. The high-resolution camera of the UAV takes pictures of crops in the area, and combines sonar sensors and multispectral sensors to obtain a vector map of the target crops based on the spectral features of the high-resolution remote sensing images. S4. Compare the vector map of the target crops based on the spectral features of the high-resolution remote sensing image with the crop growth prediction vector map, and determine the regional monitoring frequency based on the degree of agreement.

2. The information monitoring system based on rural Internet of Things according to claim 1, characterized in that, The microcontroller is connected to the storage module and the communication module via UART serial port communication.

3. The information monitoring system based on rural Internet of Things according to claim 1, characterized in that, The unmanned aerial vehicle platform is connected to the microprocessor via RS232 communication.

4. The information monitoring system based on rural Internet of Things according to claim 1, characterized in that, There are six high-resolution cameras (6).

5. The information monitoring system based on rural Internet of Things according to claim 1, characterized in that, There are two brackets (3), and the data collection mechanism (5) is located between the two brackets (3).

6. The information monitoring system based on rural Internet of Things according to claim 1, characterized in that, There are two batteries (4), and the batteries (4) are replaceable.

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