Significance: In recent years, fire hazards have been increasing yearly, and various safety factors have been interwoven and infiltrated, leading to an even more enormous fire safety (FS) pressure. However, the people have put forward higher expectations and requirements than ever for social management innovation and service optimization, including fire protection (FP) work. Social public FP usually has weak fundamental strength but faces many complex supervision objects, which brings tremendous pressure to fire management (FM) work.
Paperwork: Based on the above practical needs, the authors designed an IoT-based emergency plan information system to dispatch rescue vehicles and the emergency plan for trapped persons during a fire rescue. Firstly, the construction and application of the intelligent fire visualization platform based on 3D Geographic Information Science (GIS) are expounded, and an FMDM (fire monitoring and decision-making) system is proposed based on IoT. The platform covers project overview, equipment status, equipment classification, equipment alarm information, alarm classification, alarm statistics, equipment account information, and other modules. The live video accessed through the visual interface can clearly identify the stage of the fire, which facilitates the arrangement of rescue equipment and personnel. The vehicle scheduling model in the system primarily used two objective functions to solve the Pareto Non-Dominated Solution Set Optimization: emergency rescue time and the number of vehicles. In addition, an evacuation path optimization method based on the Improved Ant Colony (IAC) algorithm was designed to realize the dynamic optimization of building fire evacuation paths.
Experimental results: The experimental results indicate that all the values of detection signals were significantly larger in the smoldering fire scene at t = 17s than the initial value. In addition, the probability of smoldering fire and the probability of open fire were relatively large according to the probability function of the corresponding fire situation, demonstrating that this model could detect fire. In addition, The IAC algorithm avoided the passages near the fire and spreading areas as much as possible and took the safety of the trapped persons as the premise when planning the evacuation route. Therefore, the IoT-based fire information system has important value for ensuring fire safety and carrying out emergency rescue and is worthy of popularization and application.
See the article:
Intelligent Fire Information System Based on 3D GIS
https://www.sciencedirect.com/science/article/pii/S2096579622000638
