Recognition of Fire Situation Using Graph Convolutional Network Model

Fires cause a lot of casualties and economic losses. In order to prevent fire accidents in advance, it is necessary to find out the cause of the fire. Existing fire alarm systems detected fires with temperature, smoke, and flame sensors, but could not distinguish the cause of the fire. In this paper, to solve this problem, the recognition of fire situation was tested using the GCN model. The fire dataset used in the experiment is a fire dataset composed of causes such as boxes, clothing, and electricity. The accuracy of 93.44% was confirmed as a result of the learning experiment with the GCN model, a graph-based deep learning model.