Development of An Intelligent Drone Rescue System for Emergencies with Real-Time Location Transmission

Abstract

Despite advances in technology and innovations in emergency services, search and rescue (SAR) missions still encounter problems such as delay in the search for victims, high risk to human rescuers, and lack of real-time coordination in the area of disasters. In this study, the design, development, and testing of the Intelligent Drone Rescue System for Emergencies with Real-Time Location Transmission – an unmanned aerial vehicle (UAV) that seeks to solve the above-mentioned issues are presented. The proposed solution combines automated navigation by Mission Planner with Victor Sierra (Sector Search), real-time transmission of GPS coordinates, and an intelligent algorithm that uses YOLOv8 and OpenCV to classify victims into Stable, Warning, and Critical classes according to their movements observed in live video feeds. The drone prototype was assembled using an ArduPilot flight controller, Mitoot M8N GPS module, four Emax MT2213 920kv brushless motors, BLHeli 40A ESCs, a 7100mAh 3S LiPo battery, and a RunCam3 FPV camera system. The study adopted a mixed research methodology with the integration of Waterfall and Agile development methods. The evaluation of the system was undertaken by 30 experts based on ISO/IEC 25010 quality criteria through a 4-point Likert scale. The results obtained were analyzed to give a mean score of 3.38, which falls under the Strongly Agree category, implying that the system sufficiently fulfills the criteria of functional suitability, performance efficiency, usability, reliability, maintainability, and portability. In summary, the adoption of UAV technology with autonomous navigation and data communication in rescue missions will increase the speed, safety, and efficiency of such operations.