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Optimizing Tethered UAV Deployment for On-Demand Connectivity in Disaster Scenarios

Balaji Kirubakaran, Jiří Hošek

发表年份
2023
引用次数
15

摘要

Natural disasters and other emergencies can disrupt terrestrial communication infrastructure, leaving first responders and affected people without reliable connectivity. Unmanned Aerial Vehicles (UAVs) have been proposed as a promising technology for providing on-demand connectivity in such situations, but limited battery capacity remains a significant challenge. As a possible solution, Tethered UAVs (TUAVs) can extend the operation time and ensure seamless service due to their fixed connection to a ground station. In this paper, we propose a novel approach to TUAV deployment that involves using a robotic car to carry the necessary equipment for communication establishment and enable remote control by a human operator. We focus on finding the optimal locations for TUAV deployment to ensure complete user coverage and permanent connections between neighboring TUAVs. We utilize the Genetic algorithm to solve the problem of TUAV placement, considering constraints such as signal propagation models and coverage radius. The air-to-ground and air-to-air channel modeling determines the optimal perpendicular height and coverage radius of TUAVs. Our Matlab simulation results demonstrate that our proposed approach offers efficient and optimal solutions for TUAV placement using GA. This research has significant implications for disaster management and emergency response, providing a reliable and effective communication infrastructure in critical situations. Our findings can support the development of disaster response strategies and policies that incorporate TUAVs as a crucial component for on-demand connectivity solutions in disaster-affected areas. The proposed TUAV deployment approach is expected to have broad applications beyond disaster management in remote sensing, surveillance, and search and rescue operations.

关键词

Software deploymentComputer scienceEmergency managementSearch and rescueDistributed computingReal-time computing

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