RakshaNetra

RakshaNetra: IoT-Based Accident Detection, Prevention, and Alert System

RakshaNetra is an advanced IoT-based system designed to detect, prevent, and respond to critical emergencies such as fires, gas leaks, and road accidents. The system integrates multiple sensors, including the DS18B20 temperature sensor for fire detection, the MQ2 gas sensor for smoke and gas leaks, and the MPU6050 accelerometer for accident impact detection. These sensors continuously monitor environmental parameters, providing real-time data to the ESP32 microcontroller, which processes the information and triggers alerts when thresholds are exceeded.

The core of RakshaNetra's efficiency lies in its use of machine learning algorithms, such as Random Forest Regressor and Linear Regression, to analyze sensor data for anomaly detection and predictive maintenance. This enables the system to forecast potential hazards and alert users before emergencies escalate. In areas with limited internet connectivity, the ESP32 ensures seamless communication between components, maintaining system reliability.

Key features of RakshaNetra include:

• Real-Time Detection and Alerts: Immediate detection of fires, gas leaks, or accidents, with automated alerts sent to emergency responders and authorities via email or other communication channels.
• Predictive Maintenance: Machine learning-powered analysis of sensor data to predict potential system failures and anomalies.
• Remote Monitoring: Cloud-based storage and visualization of real-time sensor data, accessible via a user-friendly web interface.
• Versatility and Scalability: Suitable for homes, offices, industrial facilities, and public spaces, with the ability to integrate into existing emergency frameworks.
• Robust Communication: Operates efficiently in remote areas with poor internet connectivity, ensuring uninterrupted safety monitoring.

User Page

Admin Dashboard

Realtime dashboard with user location, current situations graphs and feedback form.