IFPSS: intelligence fire point sensing systems in AIoT environments

The situation at the scene of the fire is changing rapidly. How to collect and analyze the most immediate fire information, providing the most effective information for disaster decision-making has always been an important issue. This paper proposes an Intelligent Fire Point Sensing System (IFPSS), which proposes fire condition prediction based on artificial intelligence technology as well as large amounts of gas and temperature data in fire scenes collected by IoT devices. The IFPSS collected actual gas and temperature data from the simulation room where the actual fire test was conducted. Taking carbon monoxide (CO) and hydrogen sulfide (H2S) data as an example, the artificial intelligence analysis of IFPSS uses linear regression algorithm to establish artificial intelligence model. After training and testing the model, an accuracy of up to 84.4% predicts whether the fire process is in the very early stages of a fire.