9th International Conference on ICT for Sustainable Development

Authors - Shaswat Bhardwaj, Vyom Agrawal, Prashant Vats
Abstract - This research paper presents a comprehensive utilization of Unmanned Aerial Vehicles (UAVs) in disaster response, leveraging the YOLOv8 (You Only Look Once) object detection model for real-time human identification. The UAVs, equipped with this state-of-the-art model, efficiently capture and transmit images of human subjects to a ground station, serving as a centralized hub for further analysis. This human detection system significantly enhances situational awareness during search and rescue operations, contributing to quicker response times in disaster-stricken areas. Additionally, our UAVs are outfitted with devices designed to extend WiFi signals, thereby establishing a robust communication network in disaster zones where traditional infra-structure may be compromised. This dual-functionality approach, integrating advanced computer vision and communication technology, represents a holistic solution to the challenges faced in disaster management, positioning UAVs as versatile tools for responsive and efficient disaster response systems. This framework serves as a foundational structure, laying the groundwork for the development of more dependable, swifter disaster event detection, and energy-efficient disaster management systems based on UAV networks.