Automatic Person-in-Water Detection for Marine Search and Rescue Operations

S Rajesh; Vanka Ravi Teja; Muchakala Saileela; Vandavasi Megashyam; Yellu Bhavana; Katuru Sumanth

Automatic Person-in-Water Detection for Marine Search and Rescue Operations

Authors: S Rajesh, Vanka Ravi Teja, Muchakala Saileela, Vandavasi Megashyam, Yellu Bhavana, Katuru Sumanth

Unique Paper ID: 178099
Volume: 11
Issue: 12
PageNo: 2157-2163

Keywords: Search and Rescue (SAR) YOLOv4 Deep Learning Convolutional Neural Networks (CNN) MATLAB 2024b Drone-based Detection Computer Vision Drowning Prevention Real-time Monitoring Surveillance System Autonomous Rescue Systems Emergency Response

Abstract:
Every year, numerous individuals face life-threatening situations at sea due to accidents, vessel capsizing, or adverse weather conditions. Quick and effective rescue operations are critical to save lives, but Manual observation methods (Helicopters or Rescue boats…etc.) often face challenges like poor visibility due to bad weather conditions, vast search areas, limited resources, prone to human errors due to fatigue. Autonomous drones can be a game changing option in Search and Rescue Operations in diverse scenarios with better precision. This approach provides a reliable, scalable, and efficient solution to save lives. In our proposed system, we used CNN-based YOLOv4, a high-speed and precise object detection model on the drone captured images to detect the person in water. We achieved an accuracy of over 95% on sample images

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 12
PageNo: 2157-2163

Automatic Person-in-Water Detection for Marine Search and Rescue Operations

Available:https://ijirt.org/Article?manuscript=178099

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