Intelligent Fire Detection and Management System Using IoT and Web Technologies

Abstract

Fire accidents pose a serious threat to human lives, infrastructure, and the environment.
Rapid urbanization and industrial growth have increased the frequency and severity of fire
incidents, making efficient fire detection and management systems a necessity. Traditional
fire safety systems often rely on manual monitoring or standalone alarms, which may not
provide timely alerts or centralized control. To overcome these limitations, this project
proposes an Intelligent Fire Detection and Management System using IoT and web
technologies.
The system is designed to detect fire hazards in real time using sensor-based data such as
temperature, smoke, and gas levels. These sensors continuously monitor environmental
conditions and transmit data to a centralized system. When abnormal conditions are
detected, the system triggers alerts and notifies relevant authorities through a web-based
interface.
The backend of the system is developed using the Django framework, which handles data
processing, user management, and communication between components. The system
provides a user-friendly interface for monitoring fire conditions, managing alerts, and
coordinating emergency responses. Administrators can log in to view real-time data, track
incidents, and take necessary actions.
One of the key features of the system is its ability to provide early warning alerts, which
significantly reduces response time and minimizes damage. The system can also store
historical data for analysis, helping authorities identify patterns and improve fire
prevention strategies