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An integrated risk assessment and prediction framework for fire ignition sources in smart-green multi-unit residential buildings

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Listed:
  • Rachid Ouache

    (University of British Columbia)

  • Gyan Chhipi-Shrestha

    (University of British Columbia)

  • Kasun Hewage

    (University of British Columbia)

  • Rehan Sadiq

    (University of British Columbia)

Abstract

Fire risk in smart-green multi-unit residential buildings (SG-MURBs) is found to be causing a significant threat to public safety, property, and the environment. Therefore, this study developed a framework to assess and predict the potential ignition source factors that cause fire incidents (ISFs-FIs) in SG-MURBs. The framework consists of four steps: identification of potential ISFs-FIs; benchmarking; development of ANN model to predict ignition sources-related human factors and fire origin; and development of ANN model for fire impacts prediction. The ANN Simulink models were generated to simulate ANN models in Simulink or deploy with Simulink Coder tools using MATLAB. The developed framework was applied to seven cities in British Columbia (BC). The results identified forty key potential ISFs-FIs. The levels of relative frequency, total dollar loss, and risk of ISFs-FIs were determined and then benchmarked to identify the most critical factors. The results indicated that Vancouver, BC, has a very high fire risk level with 58%. Statistically significant (p

Suggested Citation

  • Rachid Ouache & Gyan Chhipi-Shrestha & Kasun Hewage & Rehan Sadiq, 2021. "An integrated risk assessment and prediction framework for fire ignition sources in smart-green multi-unit residential buildings," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(6), pages 1262-1295, December.
    • Handle: RePEc:spr:ijsaem:v:12:y:2021:i:6:d:10.1007_s13198-021-01231-7
    DOI: 10.1007/s13198-021-01231-7
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    References listed on IDEAS

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    1. Ali Taghi-Molla & Masoud Rabbani & Mohammad Hosein Karimi Gavareshki & Ehsan Dehghani, 2020. "Safety improvement in a gas refinery based on resilience engineering and macro-ergonomics indicators: a Bayesian network–artificial neural network approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 641-654, June.
    2. Aven, Terje & Guikema, Seth, 2011. "Whose uncertainty assessments (probability distributions) does a risk assessment report: the analysts' or the experts'?," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1257-1262.
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    Cited by:

    1. Jing Liu, 2023. "Application and research of computer aided technology in clothing design driven by emotional elements," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1691-1702, October.

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