A Novel Real-Time Unmanned Aerial Vehicles-based Disaster Management Framework

Abstract

The paper proposes a novel computing and net-working framework that can be implemented for the realization of different disaster management applications or real-time surveillance. The framework is based on networks of unmanned aerial vehicles (UAVs) equipped with different sensors including cameras. The framework represents a holistic approach that exploits the distributed architecture of clusters of UAVs and cloud computing resources located on the ground. The proposed framework is characterized by the hierarchical organization among framework elements. In such a framework, each UAV is assumed to be fully autonomous and locally implements a state-of-the-art deep learning algorithms for real-time route planning, obstacle avoidance and object detection on aerial images. The main operating modules of the proposed framework have been presented, with the emphasis on the improvements which the proposed framework can bring in terms of event detection time and accuracy, energy consumption and reliability of application in disaster management systems. The proposed framework can serve as the foundation for the development of more reliable, faster in terms of disaster event detection and energy-efficient disaster management systems based on UAV networks.