Project Abstract

Search and rescue operations are vital for saving lives in emergencies, yet they often struggle with efficient coverage of expansive areas. Integrating face detection technology with drones presents a timely and impactful solution. Real-time face detection on drones not only saves crucial time but also improves the chances of successful rescue outcomes, especially in challenging terrains or adverse conditions.This research bridges drone technology and computer vision for search and rescue applications. Its primary aim is to develop a robust system that enables drones to autonomously detect human faces in real-time during search and rescue missions. The central research question focuses on evaluating the effectiveness of drones equipped with face detection capabilities in identifying individuals across various environmental conditions.The study involves designing and implementing a system that integrates drones with face detection algorithms. It captures live video feeds from drones, processes the data using computer vision techniques such as Haar cascades or deep learning models for face detection, and provides actionable location data to rescue teams on the ground.The research showcases successful integration of face detection technology with drones, enabling rapid and accurate identification of human faces. These capabilities significantly improve situational awareness and streamline rescue efforts, ultimately contributing to more efficient and effective search and rescue operations.This work represents a significant advancement in search and rescue capabilities by leveraging the potential of drone technology and computer vision. The world gains insights into a more efficient approach for locating individuals in emergencies, bridging critical gaps in traditional methodologies and potentially saving more lives in the process.

Keywords: AI, Drones, Facial Recognition

 Conference Details

Session: Poster Session A at Poster Stand 107

Location: Sir Stanley Clarke Auditorium at Tuesday 7th 13:30 – 17:00

Markers: Betsy Dayana Marcela Chaparro Rico, Jen Pearson

Course: BSc Computer Science, 3rd Year

Future Plans: I’m looking for work