Development of an Integrated IoT-Based System for Enhanced Fire Detection and Decision-Making Using Multi-Sensor Data Analysis (Smoke, Heat, CO2)
Fire emergencies pose significant risks, necessitating rapid and accurate detection for effective response. FireSense aims to revolutionize fire safety through an innovative IoT-based solution. This project integrates multiple sensors (MQ2 for smoke, MQ135 for air quality/CO2, DHT11 for temperature and humidity, and IR for heat) into each room, controlled by ESP8266 modules. These sensors form a network of intelligent nodes that continuously monitor environmental conditions and transmit real-time data to a central Raspberry Pi 3B running Home Assistant.
The centralized system analyses data from smoke, heat, CO2, and other environmental factors, enabling faster and more informed decision-making during fire emergencies. A key feature of FireSense is the integration of a GSM module, which allows for automatic alerts to emergency services, significantly reducing response times.
Data Flow Diagram:
The centralized system analyses data from smoke, heat, CO2, and other environmental factors, enabling faster and more informed decision-making during fire emergencies. A key feature of FireSense is the integration of a GSM module, which allows for automatic alerts to emergency services, significantly reducing response times.
Our methodology includes a multi-sensor approach to capture a comprehensive range of fire indicators, a distributed network for granular, location-specific data, centralized data processing for real-time analysis, intelligent algorithms to identify patterns and anomalies, and a user-friendly Home Assistant dashboard for monitoring and control. The system's modular design ensures scalability and flexibility, making it adaptable to various building layouts and sizes.
FireSense's multi-sensor integration, distributed intelligence, open-source dashboard, automated emergency response, and cost-effective scalability make it a unique and valuable solution for enhancing fire detection accuracy, response times, and overall safety in residential and commercial settings.
By Student of UPES: Piyush Kumar, Sonali Bhadra, Dhruv Tandon, Arush Dubey