Project Demo
Project Overview
This project was developed during the 24-hour Gradient AI Hackathon conducted at B. M. S. College of Engineering, where it secured second place 🥈 out of 60 teams for its innovative approach to safety monitoring.
The Emergency Detection System is an advanced web application designed to provide real-time safety monitoring and emergency detection using Google Gemini computer vision and artificial intelligence technologies. The system utilizes Google Gemin Flash 1.5 machine learning model to identify potential emergency situations, offering immediate response mechanisms for personal safety.
The core functionality involves continuous video monitoring, detecting potential physical risks or medical emergencies through advanced image analysis. By leveraging YOLOv11 for person detection and Google Gemini AI for sophisticated scenario interpretation, the application provides a comprehensive safety monitoring solution.
Features and Functionalities
Intelligent Emergency Detection: Real-time video analysis using YOLOv11 and Google Gemini AI detects physical risks, medical emergencies, and environmental hazards.
Comprehensive Scenario Analysis: Identifies falls, immobility, breathing difficulties, and recognizes seizures, injuries, and potential obstructions.
Automated Notification System: Sends detailed emergency emails with user location and generates Google Maps links for precise location tracking.
User-Friendly Interface: Features a simple registration process, real-time status updates, and emergency popup notifications.
Flexible Detection Mechanism: Allows configurable detection intervals, continuous monitoring, and controllable start/stop functionality.