QoE-aware Airborne Communication Infrastructure for Surveillance in Wildfires

Global warming is one of the fundamental threats to all living beings today. Various side effects are triggered as a consequence of global warming. Frequent wildfires are one of the side effects causing the loss of lives, vegetation, and economies on a significant scale each year. Therefore, sophisticated mechanisms for surveilling wildfires, including communication systems that are resilient enough to transmit surveillance information to first responders even in the presence of wildfires are urgent. In this work, we leverage unmanned aerial vehicles (UAVs), cognitive radio (CR), and deep reinforcement learning (DRL) technologies to propose a Quality of Experience (QoE)-aware airborne communication infrastructure that can deliver surveillance video streams to a destination in a disaster such as wildfire. In our simulation results, we evaluate the performance of our proposed communication infrastructure by considering different scenarios.