Abstract:In the event of a fire in a building,the complex internal environment of the building and the real-time spread of the fire will bring uncertainties for efficient indoor rescue and even endanger the life of firefighters. To enhance the efficiency of indoor rescue in a building fire,a real-time rescue path planning system for firefighters is proposed in this paper based on BIM technique and cellular automata. In this system,a BIM building model and cellular automata are innovatively combined to establish a novel and intelligent cellular automata-based path planning model. This model can automatically identify varying structural components and updated internal environment of the building using scene stratification and collision detection methods,which has a high level of intelligence and generality. Based on this model,firefighters are capable of scientifically and efficiently avoiding static and dynamic obstacles and safety completing the rescue. This is achieved by creating a dynamic obstacle model and a random fire spread model,and by using a real-time detection method to account for the dynamic influence of real fire scenarios on the rescue path. Finally,simulation of a single-story large-scale stadium is conducted and the applicability of the proposed system is verified. This system aims to provide technical support for establishing rescue strategies for building fires,achieving efficient and accurate rescue and smart firefighting.