The Escape Path PlanningAlgorithm in Large Building Fires Based on Multiple Fusion Strategies

Abstract Background: Large building fires are currently the most direct and serious type of fire that causes property damage and casualties, and delayed evacuation is one of the important reasons for casualties. Therefore, how to safely and quickly evacuate trapped individuals has become the focus of research by many scholars. Our goal is to propose a robust, universal, and high-precision fire escape path that utilizes minimal human intervention, making the algorithm practical and highly fitting to the scene. Results: This article constructs a framework for evacuating and evacuating fire personnel. Through the drone relay communication platform, multi-source information data collected at the fire scene is synchronously transmitted to the information exchange center, and uploaded to the cloud for real-time processing. In the cloud processing stage, the dynamic path planning method for large-scale building fires that integrates multiple strategies proposed in this article is used to generate escape paths, and the information exchange center is used to guide personnel to evacuate and escape. In addition, the information exchange center synchronizes the comprehensive scheduling of rescue agencies such as fire alarms and emergency centers. Conclusions: This article proposes a dynamic pathfinder path planning method that integrates multiple strategies based on the original FPA. By utilizing the mapping relationship between personnel location and fitness, the path planning problem is transformed into a set sorting problem, shortening escape time and improving path safety; A multi-objective path planning mechanism based on the A * algorithm has been constructed. By defining a dynamic matching degree to adapt to environmental changes, the population density at the exit is reduced, and the algorithm's global search ability and escape efficiency are improved. A cloud server IoT fire evacuation and escape model based on relay communication drones is designed, which utilizes the drone's adaptive height characteristics to ensure communication quality while expanding communication coverage, By using cloud processing to shorten runtime, the superiority of the method was verified through comparative experiments on single objective and multi-objective global path planning under multiple sets of grid maps with different specifications.