CONFIGURING DRONES TO ESTIMATE FLOOD CHARACTERISTICS FOR TRAFFIC MANAGEMENT

Abstract

Flooding, exacerbated by climate change and global warming, poses a significant threat as one of the most prevalent natural disasters. Its direct and adverse impacts on street transportation systems lead to traffic congestion and potential harm to both individuals and vehicles. To address these challenges, the utilization of drone technology becomes imperative to mitigate damage and enhance traffic management by detecting flood characteristics such as water extent and depth on roadways. This research focuses on configuring three drones equipped with cameras to collect data through both manual and autonomous missions. Successful testing of these missions has been conducted. The collected data, in the form of videos, underwent analysis using suggested algorithms to achieve primary objectives, determining water extent and depth. The methodology relies on leveraging Google Maps data and extracting information from vehicle wheels and license plates on the streets. The outcomes of this research are promising, demonstrating the effectiveness of the proposed methodology. The successful application in real scenarios is encouraged, indicating potential for further development alongside cutting-edge technologies. This research contributes to the advancement of flood monitoring and traffic management strategies, opening avenues for continued innovation.