Fires are a major safety concern in homes and offices. Early detection of fires is critical for preventing property damage and saving lives. This project aims to build a fire detection system using gas and temperature sensors to predict when there is a fire or not.
The system will use a gas sensor to detect the presence of liquified propane gas, carbon monoxide and smoke that typically hint fire hazard. Additionally, a temperature sensor will be used to detect abnormal temperature increases and humidity decreases.
The readings from the sensors will be processed by an Arduino board that will be connected to a computer. A Python script will analyze the data, and machine learning algorithms will be used to develop a model that can predict the likelihood of a fire.
The system includes a dashboard-like interface where the end-user can get alerts for detected fires and monitor the physical and chemical quantities around the environment.
- Node.js
12.22.0+