Virtual Booth

The objective of this project is to develop an all-weather autonomous drone system equipped with advanced edge computing as well as vision-based navigation to enhance flood monitoring and emergency response capabilities. The research was carried out at Asia Pacific University, Wilayah Persekutuan Kuala Lumpur. The proposed drone system operates using AI-powered vision technology, leveraging YOLO-based object detection models deployed through Roboflow’s hosted inference API and the Mission Planner software for autonomous navigation. This integration enables real-time mapping, flood victim identification, and situational assessment. The system employs a Raspberry Pi 4 for edge computing, allowing for on-board data processing as well as faster decision-making. The system also integrates a rain sensor, barometer and IMU to enable real-time rainfall detection, altitude estimation, and stable orientation control during hovering and landing. In summary, the system improves flood response speed through autonomous navigation and intelligent data processing, while its weatherproof performance ensures reliable performance in flood-affected areas. The framework is envisioned to strengthen the advancement of disaster management technologies by providing a more proactive approach to flood mitigation.