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The purpose of this study is to develop a design for maximum area drone coverage in a post-disaster flood situation. When it comes to covering a disaster-region for monitoring and detection of the extent of damage and losses, a suitable and technically balanced approach is vital to achieving the best solution while covering the maximum affected area. Therefore, a mathematical optimisation model is proposed to effectively capture maximum images of the impacted region. The particle swarm optimisation (PSO) algorithm is used to solve the optimisation problem. Modern relief missions heavily rely on drones, specifically in the case of flooding, to capture the damage due to the disaster and to create roadmaps to help impacted people. This system has convincing results for inertia, exploration, exploitation, velocity, and determining the height of the drones to enhance the response to a disaster. The proposed approach indicates that when maintaining the flight height of the drone above 120 m, the coverage can be enhanced by approximately 34% compared with a flight height of 100 m.

Disaster Region Coverage Using Drones: Maximum Area Coverage and Minimum Resource Utilisation