Multi-factor Risk Analysis in a Building Fire by Two Step Cluster

Fire simulations and sensors are widely used in building fires, various data such as temperature, CO and CO2 concentration, visibility can be obtained by sensors and sensor-based simulation. And Injury produced by high temperature, carbon monoxide, or carbon dioxide may reduce a person's capability of judging, acting and memory. It is important to generate a risk map based on such data so that we can use it to make evacuation strategies. Using cluster analysis, likelihood distance is used to calculate the similarity of space state and danger state or safety state to get the risk level. The integrated influence of high temperature, carbon monoxide, or carbon dioxide on the occupants in a virtual building fire is dynamic analyzed to generate a risk map in the building. The dynamic risk map can realize the transformation of real-time signal to visualization risk distribution and support evacuation and rescue command.