An Efficient AI Based Ensemble Model for Human Detection and Rescue During Disaster Using UAV

Disaster management is an important to the saving people's lives. It helps to save life and respond in crucial times during disaster. This paper presents a UAV system for enhancing disaster search and rescue operations. Utilizing Ensembled HOG Human Detection System-based computer vision, the system detects humans in real-time video streams and estimates their distance from the UAV. This approach improves situational awareness for rescue teams, addressing challenges like varying lighting and occlusions. The system demonstrates high accuracy in complex scenarios, potentially expediting victim localization and improving survival rates. Future work will focus on performance enhancement in diverse environments and integration with other disaster response technologies.