Multi-role collaborative fire drill simulation with smoke risk evaluation
- 10.2991/amcce-18.2018.93How to use a DOI?
- Virtual Reality, VIZARD, KBENGINE, fire dynamics data, smoke risk evaluation model.
Fire is one of the major disasters that often happen in the cities. It causes serious economic losses and casualties. Smoke is the main cause of death in fire and it is difficult to be simulated in the traditional way of fire drill. A multi-role collaborative fire drill simulation system was developed on the basis of virtual reality and server engine technology. The system consists of the client end and the server end. In the client end, the realization of the virtual fire scenes is based on the VIZARD software, which allows the trainees to experience a realistic and yet non-threatening fire scenes. The KBENGINE framework is used to enable multi-role synchronous login, the participants can collaborate in a virtual fire drill without time or space constraints. In order to carry out effective virtual training, Fire dynamics data and three-dimensional rendering technology has been especially designed to create a realistic and accurate smoke environment. The smoke risk evaluation model was introduced to assess the safety of different evacuation routes so that trainees could identify the safest route to escape. The test results show that the system has good performance and high accuracy, which helps trainees learn the knowledge of firefighting in the low-cost, high-security, high-fidelity and repeatable virtual environment, and accumulate the real-world firefighting combat experience.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Chen Lin AU - Xiaobin Lin PY - 2018/05 DA - 2018/05 TI - Multi-role collaborative fire drill simulation with smoke risk evaluation BT - Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018) PB - Atlantis Press SP - 537 EP - 543 SN - 2352-5401 UR - https://doi.org/10.2991/amcce-18.2018.93 DO - 10.2991/amcce-18.2018.93 ID - Lin2018/05 ER -