ECMS: Energy-Efficient Collaborative Multi-UAV Surveillance System for Inaccessible Regions

Abstract

The evolution and popular adaptation of drone technology in diverse applications has necessitated advancement of UAV communication framework. UAVs inherently support features like mobility, flexibility, adaptive altitude, which make them a preferable option for dynamic surveillance of remote locations. Multiple UAVs can cooperatively work to accomplish surveillance missions more efficiently. However, the intermittent network connectivity and the limited onboard energy storage impose a great challenge on UAV-assisted remote surveillance. This paper presents an Energy-efficient Collaborative Multi-UAV Surveillance (ECMS) system for surveillance of inaccessible regions. The system employs an optimal Multi-UAV Collaborative Monocular Vision (MCMV) topology to facilitate the surveillance with zero blind spot using minimum number of drones. We also propose an application-aware Multi-Path Weighted Load-balancing (MWL) routing protocol for handling congestion by distributing traffic among all available resources in UAV network and adaptively selecting the of source datarate (i.e. switching video resolution). The simulation results demonstrate that the proposed surveillance system achieves coverage with lesser number of UAVs compared to the existing systems. It also achieves higher throughput, higher packet-delivery ratio, higher residual energy of UAVs, and lower end-to-end delay.INDEX TERMS Unmanned aerial vehicle, remote surveillance, UAV network topology, multi-path routing, load balancing.

Security Surveillance Using UAVs and Embedded Systems in Industrial Areas

“…In this work, the results attained are compared with the ones achieved by the Small-Scale Object Detection for Unmanned Aerial Vehicles (UAVs) system proposed by Saeed et al which modified the architecture of the detection network and executed on different embedded systems, as we present early our system can detect and locate the object in the surveillance area in the real-time [50]. Singhal and Barick also proposes an application-aware Multi-Path Weighted Load-balancing (MWL) routing protocol for managing congestion, this system executes its process in the ground center, which increases the processing time and makes it out of service and powerless in the event of interruption or penetration [51]. Teng et al developed a trajectory planner based on particle swarm optimization with surveillance area priority, exploiting highly consumed existing UAVs to obtain optimal trajectories [52].…”

Stackelberg game‐based task offloading in mobile edge computing‐enabled hierarchical multi‐coalition unmanned aerial vehicle networks

“…[1][2][3][4][5] Especially in civilian fields, UAVs are usually used to perform dangerous and urgent tasks in some regions where there is no ground infrastructure, such as surveillance of remote regions, disaster management, data collection, and forest fire fighting. [6][7][8][9][10] The UAV coalitions with multiple UAVs have higher processing capacity and a larger execution range than a single UAV. [11][12][13] Within each UAV coalition, a part of UAVs equipped with hardware modules are chosen to be coalition heads, and others are coalition members.…”

“…With the benefits of small size, low‐cost, great flexibility, and rapid deployment, unmanned aerial vehicles (UAVs) have been widely used in military and civilian fields 1–5 . Especially in civilian fields, UAVs are usually used to perform dangerous and urgent tasks in some regions where there is no ground infrastructure, such as surveillance of remote regions, disaster management, data collection, and forest fire fighting 6–10 . The UAV coalitions with multiple UAVs have higher processing capacity and a larger execution range than a single UAV 11–13 .…”