Intelligent Fire Information System Based on 3D GIS

This work aims to build a comprehensive and effective fire emergency management system based on the Internet of Things (IoT) and achieve an actual intelligent fire rescue. A smart fire protection information system was designed based on the IoT. A detailed analysis was conducted on the problem of re...

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Bibliographic Details
Main Authors: Jinxing Hu, Zhihan Lv, Diping Yuan, Bing He, Dongmei Yan
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2023-04-01
Series:Virtual Reality & Intelligent Hardware
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2096579622000638
Description
Summary:This work aims to build a comprehensive and effective fire emergency management system based on the Internet of Things (IoT) and achieve an actual intelligent fire rescue. A smart fire protection information system was designed based on the IoT. A detailed analysis was conducted on the problem of rescue vehicle scheduling and the evacuation of trapped persons in the process of fire rescue. The intelligent fire visualization platform based on the three-dimensional (3D) Geographic Information Science (GIS) 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. 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. The IAC algorithm reported here 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.
ISSN:2096-5796