CN-122028081-A - Dynamic monitoring method and monitoring network system for unmanned aerial vehicle remote sensing and ground sensor

CN122028081ACN 122028081 ACN122028081 ACN 122028081ACN-122028081-A

Abstract

The invention relates to the field of intelligent monitoring, and discloses a dynamic monitoring method and a monitoring network system of unmanned aerial vehicle remote sensing and ground sensors, wherein the method comprises the steps of generating a multi-dimensional temporal map of a monitoring area, extracting an abnormal mark in the multi-dimensional temporal map, matching geographic information of the abnormal mark, distributing a patrol unmanned aerial vehicle and the ground sensors for executing tasks, constructing a virtual sensor cluster by using the ground sensor, distributing monitoring tasks, building an unmanned aerial vehicle cluster by using the inspection unmanned aerial vehicle for executing the inspection task, extracting address information of each inspection unmanned aerial vehicle in the unmanned aerial vehicle cluster, planning an inspection path of the inspection unmanned aerial vehicle, executing the monitoring task by using a ground sensor and generating a real-time data packet, waking up the ground sensor when the inspection unmanned aerial vehicle executes the inspection task and flies to the corresponding ground sensor, and sending the real-time data packet to the inspection unmanned aerial vehicle by using the ground sensor.

Inventors

WANG HUIFENG
SHU HUADONG
Zu Jiaqi
YE ZHOUXING
Zhai Xuheng
LI JIANXIN
Zhao Linglin
CHEN CHENG
YU JIE
GAO HAILI
Fang Guojing
ZHANG FENG
JIN PAN
WU CHONGJIN
DUAN JUNPENG

Assignees

浙江鸿森生态科技有限公司
杭州云舟未来科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260415

Claims (10)

1. The utility model provides a dynamic monitoring method of unmanned aerial vehicle remote sensing and ground sensor which characterized in that includes: Acquiring monitoring data and remote sensing data, performing association analysis to generate a multi-dimensional temporal map of the monitoring area, extracting an abnormal mark in the multi-dimensional temporal map, and matching geographic information of the abnormal mark; Distributing a patrol unmanned aerial vehicle and a ground sensor for executing tasks, constructing a virtual sensor cluster by using a ground sensor, distributing monitoring tasks, constructing an unmanned aerial vehicle cluster by using the patrol unmanned aerial vehicle for executing the patrol tasks, extracting address information of each patrol unmanned aerial vehicle in the unmanned aerial vehicle cluster, and planning a patrol path of the patrol unmanned aerial vehicle; the ground sensor executes a monitoring task and generates a real-time data packet, the inspection unmanned aerial vehicle wakes up the ground sensor when executing the inspection task and flying to the corresponding ground sensor, the ground sensor sends the real-time data packet to the inspection unmanned aerial vehicle, the inspection unmanned aerial vehicle analyzes the real-time data packet to update the multidimensional temporal pattern, and dynamically adjusts the inspection path based on the updated multidimensional temporal pattern so as to determine the next-stage inspection path of the inspection unmanned aerial vehicle executing the inspection task.
2. The method for dynamically monitoring the remote sensing and ground sensors of the unmanned aerial vehicle according to claim 1, wherein the step of planning the inspection path of the unmanned aerial vehicle comprises the following steps: Configuring a monitoring range, forming an abnormal area by taking the position of an abnormal mark as the center and taking the monitoring range as the radius, extracting a ground sensor capable of monitoring the abnormal area, and constructing the extracted ground sensor into a virtual sensor cluster; extracting the topographic data and vegetation types of the geographic information position through the remote sensing data and the monitoring data; Determining a flight interval based on the terrain data and the vegetation type, and determining a flight attitude by combining the flight interval and the vegetation type; And constructing a patrol boundary, and determining a patrol path of the patrol unmanned aerial vehicle according to the patrol boundary.
3. The method for dynamically monitoring remote sensing and ground sensors of an unmanned aerial vehicle according to claim 2, wherein the constructing the virtual sensor cluster comprises: acquiring the identification precision of the ground sensor, extracting the effective identification range of the ground sensor, and dividing the ground sensor into monitoring levels; Determining nodes of a virtual sensor cluster based on monitoring levels, constructing edges among the nodes, dividing the nodes into standing points and supporting points, wherein the monitoring levels of the standing points are higher than the monitoring levels of the supporting points, distributing monitoring tasks of the standing points to be real-time monitoring for monitoring abnormal marks and abnormal areas, distributing monitoring tasks of the supporting points to be check monitoring for checking results of the real-time monitoring of the standing points, integrating the supporting points to generate real-time data packets, and transmitting the real-time data packets to the standing points by the supporting points through the related edges.
4. The method for dynamically monitoring the remote sensing and ground sensors of the unmanned aerial vehicle according to claim 3, wherein the standing point receives at least one real-time data packet, performs data analysis when the standing point receives a plurality of real-time data packets, and determines the real-time data packet for sending to the inspection unmanned aerial vehicle; And reversely checking whether the real-time data packet sent by the fulcrum of the sender is abnormal or not through data analysis, and sending the real-time data packet after data analysis to the fulcrum when the abnormality is identified.
5. The method for dynamically monitoring the remote sensing and ground sensor of the unmanned aerial vehicle according to claim 4, wherein the unmanned aerial vehicle is provided with a photoelectric pod and a side view radar, the identification angle of the photoelectric pod and the fan-scan angle of the side view radar are obtained, the gradient and the slope direction in the topographic data are extracted, the flying layer for the unmanned aerial vehicle to execute the monitoring task in the abnormal area is determined according to the vegetation type, and the flying layer and the topographic data are fitted to determine the flying interval; Determining slope surface normals of the terrain through the gradient and the slope direction, adjusting the identification angle and the fan scanning angle, calculating the included angle between the inspection unmanned aerial vehicle and the slope surface normals, and adjusting the pitch angle of the inspection unmanned aerial vehicle so as to adjust the flight attitude of the inspection unmanned aerial vehicle; The coverage of the ground sensor serving as a residence point is extracted, the terrain data are fused to form a safety boundary, a constrained flight space is constructed, and the flight space is optimized through the task efficiency of the ground sensor to form a patrol boundary.
6. The method for dynamically monitoring remote sensing and ground sensors of an unmanned aerial vehicle according to claim 5, wherein adjusting the pitch angle of the inspection unmanned aerial vehicle comprises: Comparing the current course of the inspection unmanned aerial vehicle with the slope direction; If the heading is consistent with the steepest rising direction of the slope, setting the expected pitch angle to be equal to the gradient value; if the heading is consistent with the direction of the contour line, setting the expected pitch angle to be zero; if the pitch angle is other course, carrying out interpolation calculation according to the included angle between the course and the steepest direction, and determining the expected pitch angle.
7. The method of dynamic monitoring of unmanned aerial vehicle remote sensing and ground sensors of claim 6, wherein constructing the patrol boundary comprises: Determining a link space for establishing communication connection between the inspection unmanned aerial vehicle and a ground sensor serving as a standing point; identifying a distance between the flight layer and the stagnation point; and adjusting the height of the flight layer or the communication power of the standing point based on the intersection condition of the distance and the link space so as to construct the inspection boundary.
8. The method of dynamic monitoring of unmanned aerial vehicle remote sensing and ground sensors of claim 7, wherein planning the routing path further comprises: Identifying a blank area which cannot be covered by the surface sensor in the monitoring area, and dividing the inspection priority according to the residual electric quantity or the task state of the inspection unmanned aerial vehicle; and distributing a specific inspection path for each inspection unmanned aerial vehicle in the unmanned aerial vehicle cluster based on the characteristics of the blank area, the distribution of standing points and supporting points and the inspection priority.
9. The method of dynamic monitoring of unmanned aerial vehicle remote sensing and ground sensors of claim 1, wherein waking up the ground sensor comprises: After entering the communication range of the target ground sensor, the patrol unmanned aerial vehicle sends a wake-up signal carrying a unique identifier of the target ground sensor; the target ground sensor receives and analyzes the wake-up signal through a low-power wake-up receiver, and wakes up from a sleep state and starts a main communication module after the identifiers are successfully matched; and the target ground sensor establishes a communication link with the inspection unmanned aerial vehicle and performs identity authentication.
10. A dynamic monitoring network system of unmanned aerial vehicle remote sensing and ground sensors for performing the method of any one of claims 1 to 9, comprising: the fusion monitoring module is used for acquiring monitoring data and remote sensing data and carrying out association analysis to generate a multi-dimensional temporal map of the monitoring area; the anomaly identification module is used for extracting anomaly marks in the multi-dimensional temporal map and matching geographic information of the anomaly marks; The task allocation module is used for allocating the patrol unmanned aerial vehicle and the ground sensor to execute tasks, constructing a virtual sensor cluster by a ground sensor, allocating monitoring tasks and constructing an unmanned aerial vehicle cluster for executing the patrol tasks; the path planning module is used for extracting address information of each inspection unmanned aerial vehicle in the unmanned aerial vehicle cluster and planning an inspection path by combining the geographic information; The data interaction module is used for controlling the ground sensor to execute a monitoring task and generate a real-time data packet, and the inspection unmanned aerial vehicle wakes the ground sensor and receives the real-time data packet sent by the ground sensor when flying against the corresponding ground sensor; And the map updating module is used for analyzing the real-time data packet to update the multidimensional temporal map, dynamically adjusting the routing inspection path based on the updated map and determining the path for executing the routing inspection task at the next stage.

Description

Dynamic monitoring method and monitoring network system for unmanned aerial vehicle remote sensing and ground sensor Technical Field The invention relates to a dynamic monitoring method and a monitoring network system for remote sensing and ground sensors of an unmanned aerial vehicle, and belongs to the technical field of intelligent monitoring. Background The existing forestry and water resource inspection monitoring system generally adopts unmanned aerial vehicles to periodically inspect along a route or carry out static detection on a fixed ground sensor network, signals are sent to a central gateway to alarm when abnormal events are monitored, the mode has inherent defects, the unmanned aerial vehicles inspect the system and have space-time dead zones, the events which occur in the intermittent period of flight cannot be captured timely to cause incomplete monitoring, the coverage of the fixed sensor network is limited, the condition of monitoring misalignment is caused when the sensor range is exceeded or the sensor is close to the monitoring edge, the sensor needs to continuously keep the performance of monitoring and communication, meanwhile, the sensor is powered by a built-in power supply mode, the sensor is easy to lack the ionization line, and partial area monitoring is easy to lose, so that intelligent coordination and full monitoring response are not realized. Meanwhile, the unmanned aerial vehicle and the ground sensor data are mutually independent and are linked by the central gateway, the deep fusion and joint reasoning between the unmanned aerial vehicle and the sensors are lacked, and the central gateway relies on manual interpretation, so that the chain length of a signal which responds to the sensing is caused, the monitoring efficiency is low, the signal processing time under the emergency is long, and the prevention and control response cannot be timely made. Disclosure of Invention The invention aims to provide a dynamic monitoring method and a monitoring network system for remote sensing and ground sensors of an unmanned aerial vehicle, wherein the sensors and the unmanned aerial vehicle are dynamically networked to form virtual sensor clusters for monitoring and sensing, a patrol path of the unmanned aerial vehicle is dynamically planned, and wireless energy supply is carried out on the sensors through the unmanned aerial vehicle. In order to achieve the above purpose/solve the above technical problems, the present invention is realized by adopting the following technical scheme. In one aspect, the invention provides a method for dynamically monitoring remote sensing and ground sensors of an unmanned aerial vehicle, which comprises the following steps: Acquiring monitoring data and remote sensing data, performing association analysis to generate a multi-dimensional temporal map of the monitoring area, extracting an abnormal mark in the multi-dimensional temporal map, and matching geographic information of the abnormal mark; Distributing a patrol unmanned aerial vehicle and a ground sensor for executing tasks, constructing a virtual sensor cluster by using a ground sensor, distributing monitoring tasks, constructing an unmanned aerial vehicle cluster by using the patrol unmanned aerial vehicle for executing the patrol tasks, extracting address information of each patrol unmanned aerial vehicle in the unmanned aerial vehicle cluster, and planning a patrol path of the patrol unmanned aerial vehicle; the ground sensor executes a monitoring task and generates a real-time data packet, the inspection unmanned aerial vehicle wakes up the ground sensor when executing the inspection task and flying to the corresponding ground sensor, the ground sensor sends the real-time data packet to the inspection unmanned aerial vehicle, the inspection unmanned aerial vehicle analyzes the real-time data packet to update the multidimensional temporal pattern, and dynamically adjusts the inspection path based on the updated multidimensional temporal pattern so as to determine the next-stage inspection path of the inspection unmanned aerial vehicle executing the inspection task. Preferably/further, the planning of the inspection path of the inspection unmanned aerial vehicle specifically includes: Configuring a monitoring range, forming an abnormal area by taking the position of an abnormal mark as the center and taking the monitoring range as the radius, extracting a ground sensor capable of monitoring the abnormal area, and constructing the extracted ground sensor into a virtual sensor cluster; extracting the topographic data and vegetation types of the geographic information position through the remote sensing data and the monitoring data; Determining a flight interval based on the terrain data and the vegetation type, and determining a flight attitude by combining the flight interval and the vegetation type; And constructing a patrol boundary, and determining a patrol path of the patrol unmanned aerial