IOT BASED REAL TIME BOREWELL VICTIM DETECTION AND RESCUE ROBOT

Abstract

Borewell accidents are among the most tragic incidents affecting children worldwide, particularly in rural and semi-urban areas where open borewells pose significant safety hazards. These accidents often result in fatalities due to delayed detection and the complexity of rescue operations. This project presents an IoT-based real-time borewell victim detection and rescue system that integrates advanced sensors, embedded systems, and actuators to provide a comprehensive solution for rapid victim identification and rescue. The system employs a DHT11 sensor for temperature and humidity monitoring, an ESP-CAM module for real-time visual surveillance, a smoke sensor for detecting hazardous gases, and an ultrasonic sensor for measuring depth and detecting the presence of victims. The core processing is handled by an Arduino microcontroller programmed with custom software algorithms. Upon detection, the system triggers multiple alert mechanisms including an LCD display for real-time information, a buzzer for audio alerts, and LED indicators for visual warnings. The rescue operation is facilitated by a robotic arm mechanism powered by a DC motor, enabling safe retrieval of victims without human intervention in dangerous zones. The entire system is connected through IoT technology, allowing remote monitoring and control via cloud platforms, enabling rescue teams to access critical information instantly from any location. This automated approach significantly reduces response time, minimizes human risk during rescue operations, and increases survival rates through immediate detection and intervention capabilities. Keywords— Borewell Safety, IoT Monitoring, Victim Detection, ESP32-CAM, Robotic Rescue Arm.