Abstract: [Objective] A laboratory is an important place for scientific research and teaching in colleges and universities, with dense personnel, many types of dangerous sources, and a high incidence of accidents. Thus, it is also the focus of fire safety. The indicating direction of current fire evacuation instruction systems is fixed and cannot adjust the current best escape route according to the fire situation in real time. It can easily guide people to fires in complex buildings, greatly increasing the evacuation risk, and apparently cannot meet actual needs. Therefore, designing a laboratory intelligent fire emergency evacuation system based on the coordination of monitoring and path simulation is extremely necessary to realize internal fire information collection and intelligent evacuation direction guidance in laboratory scenes. [Methods] First, the overall scheme and function of the system are designed. The system is composed of a fire information sensing indicator and an intelligent evacuation decision-making terminal. The fire information sensor indicator uses an STM32 microprocessor as the main control. It collects smoke, temperature, and other sensor information and then determines the fire situation by comparing the data with threshold values. In this paper, an intelligent indicator with adjustable direction is designed. It can change the direction of the evacuation indication by controlling the LED background light to turn on or turn off. The intelligent evacuation decision-making terminal is connected to the image acquisition system. Through machine vision, the contours of the head and shoulders of the human body are identified on the basis of the YOLOv5s framework. Therefore, the human flow is monitored. On this basis, Pathfinder is used to establish a physical model and personnel distribution model of the laboratory building. It simulates the personnel evacuation plan, obtains the theoretical optimal evacuation route, and calculates the evacuation indication direction in the scene using an intelligent algorithm. Then, the software program controls the direction of the emergency evacuation indicator light. Finally, the system verifies the guiding effect in real time. It controls the direction of the emergency evacuation indicator light according to the change in the fire situation and forms a new safety evacuation network to achieve the purpose of intelligent evacuation. It is aimed at the shortest total escape time for personnel in the laboratory building. QT Creator is used to construct the entire central control system. [Results] This system can accurately monitor fire information, obtain statistics on human flow in laboratory buildings, trigger the alarm when a fire occurs, optimize the emergency evacuation path according to the Pathfinder simulation and system monitoring results, adjust the direction of the evacuation indicator, and reduce the evacuation time. Through comparison with other cases, it is found that without intelligent guidance, people actively choose the nearest exit, and congestion occurs. When there is intelligent guidance, the optimal path is selected to avoid congestion in evacuation. Therefore, the evacuation time in the two scenarios with intelligent guidance is reduced by 19.95% and 12.71%, respectively, compared with that without intelligent guidance. [Conclusions] According to the above research, the laboratory intelligent fire emergency evacuation system based on the coordination of monitoring and simulation has achieved good results in fire information monitoring, evacuation flow detection, intelligent dynamic evacuation path planning and personnel evacuation guidance. It can greatly improve emergency evacuation ability during fires and has promotion value in complex buildings. [ABSTRACT FROM AUTHOR]
Processing Request
No Comments.