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Interactive WebVR visualization for online fire evacuation training

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Abstract

Online training is necessary for public fire escaping with the development of WebVR (Virtual Realization on Web). However, the online real-time fire training could not implemented in WebVR for the large-scale public scenario because of the huge size of VR fire scenario data, the low network transmission speed, and the slowly rendering ability of Web browser. To solve these bottlenecks, we propose a suite of solution for WebVR online fire training. Firstly, we implement a series of lightweight technologies to compress the large-scale scene data. The huge BIM (Building Information Modeling) volume data could be compressed by as much as 10 times. Then, we propose a kind of FDS (Fire Dynamic Simulator) smoking data lightweight mechanism to compress huge volume smoke data, which can be reduced by as much as 30 times. Thirdly, we adopt the multithread loading mechanism to accelerate WebVR fire scenario lightweight data. Finally, we collect the escape traces from history fire evacuation of the public, who wear the VR devices. Based on the valuable traces, we propose the TC-eACO algorithm to plan crowd optimal evacuation paths. At the same time, we implement a prototype system based on TC-eACO for WebVR fire evacuation training, with which the user just needs to surf the internet and take part in the fire evacuation training. The experimental results demonstrate that the solutions we proposed are feasible for online fire evacuation training not only in subway stations but also in other types of buildings.

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Acknowledgments

The authors appreciate the comments and suggestions of all the anonymous reviewers, whose comments help the authors significantly in their revising the paper. We thank Ming Li for her contribution in language modification of this paper. This work is supported by the Key Research Projects of Central University of Basic Scientific Research Funds for Cross Cooperation (201510-02 and 201710-04).

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Authors and Affiliations

  1. School of Electronic and Electrical Engineering, Shanghai University of Engeering Science, Shanghai, 201826, China

    Fengting Yan, Zhicai Shi & Xiang Liu

  2. School of Software Engineering, Tongji University, Shanghai, 201804, China

    Yonghao Hu & Jinyuan Jia

  3. Changchun University of Science and Technology, school of computer science and technology, Jilin, 130022, China

    Zihao Ai

  4. Hong Kong University of Science and Technology, Hongkong, 999077, China

    Kai Tang

  5. Shanghai Key Laboratory of Integrated Administration Technologies for Information Security, Shanghai, 200240, China

    Zhicai Shi

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  1. Fengting Yan
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  2. Yonghao Hu
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  4. Zihao Ai
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  5. Kai Tang
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  7. Xiang Liu
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Correspondence to Fengting Yan.

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Yan, F., Hu, Y., Jia, J. et al. Interactive WebVR visualization for online fire evacuation training. Multimed Tools Appl 79, 31541–31565 (2020). https://doi.org/10.1007/s11042-020-08863-0

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  • DOI: https://doi.org/10.1007/s11042-020-08863-0

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