Multi-machine cooperative unmanned aerial vehicle safety monitoring control system

Abstract

The invention discloses a multi-aircraft cooperative unmanned aerial vehicle safety monitoring control system, and the system comprises a cooperative control module which is responsible for generating a multi-aircraft cooperative flight strategy, and guaranteeing the efficient cooperation of all unmanned aerial vehicles in a monitoring task. The module is based on a deep learning algorithm, carries out real-time analysis on the state, environment information and the like of an unmanned aerial vehicle cluster, and dynamically adjusts a flight strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) control and safety monitoring, and in particular to an unmanned aerial vehicle (UAV) safety monitoring and control system capable of realizing multi-machine collaborative operation. Background Art

[0002] With the continuous advancement of drone technology, their application in security monitoring is increasing. However, existing drone security monitoring systems typically rely on the independent operation of a single drone, which in some cases may not meet the needs of large-scale, efficient security monitoring. Furthermore, single drones may have monitoring blind spots or insufficient response in complex or emergency situations. Therefore, developing a drone security monitoring control system that can achieve multi-drone collaboration to improve monitoring efficiency, reduce blind spots, and enhance system robustness has become a key direction of current technological development. Summary of the Invention

[0003] To address the shortcomings of existing technologies, the present invention provides a multi-drone collaborative UAV safety monitoring and control system, addressing network security concerns. To achieve the above objectives, the present invention is implemented through the following technical solutions: A multi-drone collaborative UAV safety monitoring and control system utilizes a collaborative control algorithm to enable coordinated operation of multiple drones, thereby improving the efficiency and accuracy of safety monitoring. A drone swarm consists of multiple autonomous drones, each equipped with high-definition cameras, sensors, and other data acquisition equipment. A collaborative control module generates multi-drone collaborative flight strategies to ensure efficient collaboration among the drones during monitoring missions. Based on a deep learning algorithm, this module dynamically adjusts flight strategies through real-time analysis of the drone swarm's status and environmental information. A data processing and analysis module receives and processes data collected by each drone, extracting key information relevant to safety monitoring. This module utilizes advanced image processing and data mining technologies for real-time analysis and early warning of monitoring data. A communication module ensures real-time and accurate information transmission and command issuance between the drone swarm and the control center.

Claims

1. The present invention provides a multi-machine cooperative UAV safety monitoring and control system, which realizes the cooperative operation of multiple UAVs through a cooperative control algorithm to improve the efficiency and accuracy of safety monitoring. It is characterized by: Includes: Drone swarm: composed of multiple drones with autonomous flight capabilities, each equipped with high-definition cameras, sensors and other data acquisition equipment.

2. The multi-drone collaborative safety monitoring and control system according to claim 1 includes a collaborative control module responsible for generating multi-drone collaborative flight strategies to ensure efficient collaboration among drones during monitoring missions. This module, based on a deep learning algorithm, dynamically adjusts flight strategies through real-time analysis of the drone cluster's status and environmental information.

3. The multi-drone coordinated safety monitoring and control system according to claim 1 includes a data processing and analysis module responsible for receiving and processing data collected by each drone and extracting key information related to safety monitoring. This module uses advanced image processing and data mining technologies to perform real-time analysis and early warning of monitoring data.

4. The multi-machine cooperative UAV safety monitoring and control system according to claim 1 is characterized by comprising a communication module: responsible for data transmission and command issuance between the UAV cluster and the control center to ensure the real-time and accuracy of information.