An Energy-Efficient Swarm-based Unmanned Aerial Vehicle System for Mobile Object Tracking and Video Delivery in Disaster Scenarios
UAV, tracking, video, energy-aware
Floods are the most common disaster in the world and cause deaths, damages to houses, buildings, and possessions, as well as disruption to communications. In such scenarios, it is needed to search and track mobile objects transported by the water flows, such as humans, animals, vehicles, and debris. Unmanned Aerial Vehicles (UAVs) appears as an essential tool in disaster scenarios, in order to help first responders to determine correct procedures in terms of searching, tracking, and rescuing the victims, as well as in defining the actions to minimize the risks in a sustainable and timely manner. However, the tracking of mobile objects and the delivery of real-time video sequences from UAVs with energy constraints toward first responders is still a hard task. Therefore, it is necessary to orchestrate a swarm of UAVs for searching and tracking mobile objects while reacting fast to frequent changes in the topology and trajectory, as well as distributing real-time video flows with quality level support to the ground team. This thesis presents an energy-efficient swarm-based scheme for mobile object tracking, called SUAV (Swarm of UAVs). The SUAV provides a unique UAV-based system for rescue scenarios with mobile objects and with support for route and path planning, searching and tracking procedures, mobility prediction and multi-hop communication management, video delivery with quality level support, and energy-efficiency. Simulation results show that SUAV transmitted videos with at least 15% better QoE support while minimizing the energy consumption by at least 22% when compared to related works.