Skip to main content
SpringerLink
Log in

Smart Safety Design for Firefighting, Evacuation, and Rescue

  • Chapter
  • First Online:
Intelligent Building Fire Safety and Smart Firefighting

  • 412 Accesses

Abstract

Fire is a vital threat to both occupants inside the building and firemen during their firefighting and rescue operation. Once a fire occurs, building environment changes rapidly, showing high temperature, toxic gas composition, low luminance and visibility. The occupants in a confined fire environment need to evacuate before reaching untenable conditions. Specific fire safety design of buildings has been required for fire evacuation over the last decades. To design a safe fire evacuation, conventional approaches rely on prescriptive codes or performance-based design. On top of that, with the booming of emerging technologies and thorough understanding of human behavior, smart design is increasingly welcome and applied to evacuation such as artificial intelligence evacuation modelling and real-time guidance systems However, few design considerations are given to firefighters who enter fire scenes and are exposed to more dangerous environment. Considering the firefighting and rescuing of trapped occupants, building fire safety design should include firefighting facilities and exclusive paths following specific codes, and corresponding safe firefighting principles for firefighters’ operation according to principles for evacuation. Similarly, smart design should be applied in firefighting and rescue including automatic firefighting facilities, intelligent early warning systems. Thus, this chapter provides an overview of the fire safety design progress for evacuation, firefighting and rescue using both conventional and smart approaches. Specifically, it introduces smart fire safety design development and discusses their perspectives and challenges.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. S.T. McKenna, N. Jones, G. Peck, K. Dickens, W. Pawelec, S. Oradei, S. Harris, A.A. Stec, T.R. Hull, Fire behaviour of modern façade materials—understanding the Grenfell Tower fire. J. Hazard. Mater. 368, 115–123 (2019). https://doi.org/10.1016/j.jhazmat.2018.12.077

    Article  Google Scholar 

  2. K. Fridolf, D. Nilsson, H. Frantzich, Fire evacuation in underground transportation systems: a review of accidents and empirical research. Fire Technol. 49, 451–475 (2013)

    Article  Google Scholar 

  3. Y. Zhang, Z. Yan, H. Zhu, Y. Shen, Q. Guo, Q. Guo, Experimental investigation of pedestrian evacuation using an extra-long steep-slope evacuation path in a high altitude tunnel fire. Sustain. Cities Soc. 46, 101423 (2019). https://doi.org/10.1016/j.scs.2019.101423

    Article  Google Scholar 

  4. A. Cowlard, A. Bittern, C. Abecassis-Empis, J. Torero, Fire safety design for tall buildings, in Procedia Eng, Elsevier Ltd. (2013), pp. 169–181. https://doi.org/10.1016/j.proeng.2013.08.053

  5. S.E. Magnusson, H. Frantzich, K. Harada, Fire safety design based on calculations: uncertainty analysis and safety verification. Fire Saf. J. 27, 15–334 (1996)

    Google Scholar 

  6. A.H. Buchanan, Implementation of performance-based fire codes. Fire Saf. J. 32, 377–383 (1999)

    Article  Google Scholar 

  7. Y.E. Kalay, Performance-based design. Autom. Constr. 8, 395–409 (1999)

    Article  Google Scholar 

  8. C.M. Fleischmann, Is prescription the future of performance-based design? in Fire Safety Science (2011), pp. 77–94. https://doi.org/10.3801/IAFSS.FSS.10-77

  9. G. Spinardi, Fire safety regulation: prescription, performance, and professionalism. Fire Saf. J. 80, 83–88 (2016). https://doi.org/10.1016/j.firesaf.2015.11.012

    Article  Google Scholar 

  10. A.A. Sheeba, R. Jayaparvathy, Performance modeling of an intelligent emergency evacuation system in buildings on accidental fire occurrence. Saf. Sci. 112, 196–205 (2019). https://doi.org/10.1016/j.ssci.2018.10.027

    Article  Google Scholar 

  11. M.P. Manuel, M. Faied, M. Krishnan, M. Paulik, Robot platooning strategy for search and rescue operations. Intell. Serv. Robot. (2021). https://doi.org/10.1007/s11370-021-00390-7

    Article  Google Scholar 

  12. X. Zhang, Z. Tang, Z. Fang, L. Zhang, Assessment of emergency evacuation in tunnel fire environment, in 2016 International Conference on Robots & Intelligent System (ICRIS) (2016), pp. 128–131. https://doi.org/10.1109/icris.2016.27

  13. Y. Zhang, W. Li, Y. Rui, S. Wang, H. Zhu, Z. Yan, A modified cellular automaton model of pedestrian evacuation in a tunnel fire. Undergr. Space Technol. 130 (2022) https://doi.org/10.1016/j.tust.2022.104673.

  14. E. Duarte, F. Rebelo, J. Teles, M.S. Wogalter, Behavioral compliance for dynamic versus static signs in an immersive virtual environment. Appl. Ergon. 45, 1367–1375 (2014). https://doi.org/10.1016/j.apergo.2013.10.004

    Article  Google Scholar 

  15. H. Yin Wong, Y. Zhang, X. Huang, A review of dynamic directional exit signage: challenges and perspectives (2022). www.nfpa.org/foundation

  16. E. Vilar, F. Rebelo, P. Noriega, E. Duarte, C.B. Mayhorn, Effects of competing environmental variables and signage on route-choices in simulated everyday and emergency wayfinding situations. Ergonomics 57, 511–524 (2014). https://doi.org/10.1080/00140139.2014.895054

    Article  Google Scholar 

  17. Y. Zhang, X. Huang, A review of tunnel fire evacuation strategies and state-of-the-art research in China. Fire Technol. (2022). https://doi.org/10.1007/s10694-022-01357-5

    Article  Google Scholar 

  18. A. Haghighat, K. Luxbacher, Tenability analysis for improvement of firefighters’ performance in a methane fire event at a coal mine working face. J. Fire Sci. 36, 256–274 (2018). https://doi.org/10.1177/0734904118767066

    Article  Google Scholar 

  19. L. Bel-Latour, M.A. Granié, The influence of the perceived masculinity of an occupation on risk behavior: the case of firefighters. Saf Sci. 150 (2022). https://doi.org/10.1016/j.ssci.2022.105702

  20. Y. Zhang, X. Zhang, X. Huang, Design a safe firefighting time (SFT) for major fire disaster emergency response. Int. J. Disaster Risk Reduct. 88 (2023). https://doi.org/10.1016/j.ijdrr.2023.103606

  21. F. Tao, Q. Qi, L. Wang, A.Y.C. Nee, Digital twins and cyber–physical systems toward smart manufacturing and industry 4.0: correlation and comparison. Engineering 5, 653–661 (2019). https://doi.org/10.1016/j.eng.2019.01.014

  22. L. chu Su, X. Wu, X. Zhang, X. Huang, Smart performance-based design for building fire safety: prediction of smoke motion via AI. J. Build. Eng. 43 (2021). https://doi.org/10.1016/j.jobe.2021.102529

  23. P. Reneke, C. Grant, N.P. Bryner, A.W. Jones, G.H. Koepke, in Research Roadmap for Smart Fire Fighting, Gaithersburg, MD (2015). https://doi.org/10.6028/NIST.SP.1191

  24. N. Naraghiaraghi, Z. Feng, R. Lovreglio, S. Wilkinson, Combining BIM and VR for future earthquake damage assessment training tools A REVIEW OF THE IMPACTS OF COVID-19 ON THE CONSTRUCTION INDUSTRY IN AUCKLAND, NEW ZEALAND View project Building Quake & People-a serious game platform for informing life saving strategies View project Combining BIM and VR for future earthquake damage assessment training tools (2022). https://www.researchgate.net/publication/358808115

  25. Bateman, Edwards, Gender and Evacuation_ A Closer Look at Why Women Are More Likely to Evacuate for Hurricanes (n.d.)

    Google Scholar 

  26. M. Kobes, I. Helsloot, B. de Vries, J.G. Post, N. Oberijé, K. Groenewegen, Way finding during fire evacuation; an analysis of unannounced fire drills in a hotel at night. Build. Environ. 45, 537–548 (2010). https://doi.org/10.1016/j.buildenv.2009.07.004

    Article  Google Scholar 

  27. S.L. Poon, A dynamic approach to ASET/RSET assessment in performance based design, in Procedia Eng, Elsevier Ltd. (2014), pp. 173–181. https://doi.org/10.1016/j.proeng.2014.04.025

  28. Y. Zhu, T. Chen, N. Ding, M. Chraibi, W.C. Fan, Follow the evacuation signs or surrounding people during building evacuation, an experimental study. Phys. A: Stat. Mech. Its Appl. 560 (2020). https://doi.org/10.1016/j.physa.2020.125156

  29. J. Norén, M. Delin, K. Fridolf, Ascending stair evacuation: what do we know? Transp. Res. Procedia 2, 774–782 (2014). https://doi.org/10.1016/j.trpro.2014.09.087

    Article  Google Scholar 

  30. E. Ronchi, Testing the predictive capabilities of evacuation models for tunnel fire safety analysis. Saf. Sci. 59, 141–153 (2013). https://doi.org/10.1016/j.ssci.2013.05.008

    Article  Google Scholar 

  31. PIARC, Safety in tunnels: transport of dangerous goods through road tunnels, OECD (1999)

    Google Scholar 

  32. H. Hou, L. Wang, Measuring the rationality in evacuation behavior with deep learning (2021). https://doi.org/10.3390/e24020198

  33. Y. Chen, S. Hu, H. Mao, W. Deng, X. Gao, Application of the best evacuation model of deep learning in the design of public structures. Image Vis. Comput. 102 (2020). https://doi.org/10.1016/j.imavis.2020.103975

  34. D. Xu, X. Huang, J. Mango, X. Li, Z. Li, Simulating multi-exit evacuation using deep reinforcement learning. Trans. GIS 25, 1542–1564 (2021). https://doi.org/10.1111/tgis.12738

    Article  Google Scholar 

  35. H.H. Yen, C.H. Lin, H.W. Tsao, Time-aware and temperature-aware fire evacuation path algorithm in IOT-enabled multi-story multi-exit buildings. Sensors (Switzerland). 21, 1–24 (2021). https://doi.org/10.3390/s21010111

    Article  Google Scholar 

  36. T. Zhang, Z. Wang, Y. Zeng, X. Wu, X. Huang, F. Xiao, Building artificial-intelligence digital fire (AID-fire) system: a real-scale demonstration. J. Build. Eng. 62, 105363 (2022). https://doi.org/10.1016/j.jobe.2022.105363

  37. X. Wu, X. Zhang, X. Huang, F. Xiao, A. Usmani, A real-time forecast of tunnel fire based on numerical database and artificial intelligence. Build. Simul. 15, 511–524 (2022). https://doi.org/10.1007/S12273-021-0775-X/METRICS

    Article  Google Scholar 

  38. Z. Wang, T. Zhang, X. Huang, Predicting real-time fire heat release rate by flame images and deep learning. Proc. Combust. Inst. (2022). https://doi.org/10.1016/j.proci.2022.07.062

  39. G. Zhang, D. Lu, H. Liu, IoT-based positive emotional contagion for crowd evacuation. IEEE Internet Things J. 8, 1057–1070 (2021). https://doi.org/10.1109/JIOT.2020.3009715

    Article  Google Scholar 

  40. S. Li, L. Tong, C. Zhai, Extraction and modelling application of evacuation movement characteristic parameters in real earthquake evacuation video based on deep learning. Int. J. Disaster Risk Reduct. 80 (2022). https://doi.org/10.1016/j.ijdrr.2022.103213

  41. G. Cosma, E. Ronchi, D. Nilsson, Way-finding lighting systems for rail tunnel evacuation: a virtual reality experiment with Oculus Rift®. J. Transp. Saf. Secur. 8, 101–117 (2016). https://doi.org/10.1080/19439962.2015.1046621

    Article  Google Scholar 

  42. G.-Y. Jeon, J.-Y. Kim, W.-H. Hong, G. Augenbroe, Evacuation performance of individuals in different visibility conditions. Build. Environ. 46, 1094–1103 (2011). https://doi.org/10.1016/j.buildenv.2010.11.010

    Article  Google Scholar 

  43. I. RodrĂ­guez-GarzĂłn, M. MartĂ­nez-Fiestas, A. Darmohraj, A. Delgado-Padial, R. Chumpitaz, Voluntary and involuntary risk acceptance: a case study of firefighters. Saf. Sci. 142 (2021). https://doi.org/10.1016/j.ssci.2021.105394

  44. M. MartĂ­nez-Fiestas, I. RodrĂ­guez-GarzĂłn, A. Delgado-Padial, Firefighter perception of risk: a multinational analysis. Saf. Sci. 123 (2020). https://doi.org/10.1016/j.ssci.2019.104545

  45. B.W. Butler, J.D. Cohen, Firefighter safety zones: a theoretical model based on radiative heating. Int. J. Wildland Fire 8, 73–77 (1998). https://doi.org/10.1071/WF9980073

    Article  Google Scholar 

  46. P.E. Dennison, G.K. Fryer, T.J. Cova, Identification of firefighter safety zones using lidar. Environ. Model. Softw. 59, 91–97 (2014). https://doi.org/10.1016/j.envsoft.2014.05.017

    Article  Google Scholar 

  47. X. Wu, X. Zhang, Y. Jiang, X. Huang, G.G.Q. Huang, A. Usmani, An intelligent tunnel firefighting system and small-scale demonstration. Tunn. Undergr. Space Technol. 120, 104301 (2022). https://doi.org/10.1016/j.tust.2021.104301

    Article  Google Scholar 

Download references

Acknowledgements

This work is funded by the National Natural Science Foundation of China (52204232), the MTR Research Fund (PTU-23005), and the Hong Kong Research Grants Council Theme-based Research Scheme (T22-505/19-N).

Author information

Authors and Affiliations

  1. Department of Geotechnical Engineering, Tongji University, Shanghai, China

    Yuxin Zhang

  2. Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China

    Xinyan Huang

Authors
  1. Yuxin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xinyan Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuxin Zhang .

Editor information

Editors and Affiliations

  1. Department of Building Environment and Energy Engineering, Hong Kong Polytechnic University, Kowloon, Hong Kong

    Xinyan Huang

  2. Fire Research Division, National Institute of Standards and Technology, Gaithersburg, MD, USA

    Wai Cheong Tam

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Zhang, Y., Huang, X. (2024). Smart Safety Design for Firefighting, Evacuation, and Rescue. In: Huang, X., Tam, W.C. (eds) Intelligent Building Fire Safety and Smart Firefighting. Digital Innovations in Architecture, Engineering and Construction. Springer, Cham. https://doi.org/10.1007/978-3-031-48161-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-48161-1_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48160-4

  • Online ISBN: 978-3-031-48161-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation