Blockchain for fire-risk reduction in long-scale tunnel construction
DOI: https://doi.org/10.3846/jcem.2025.25511Abstract
Tunnel construction fire risk reduction is an integral component for tunnel construction safety. Recent fire cases during tunnel construction illustrate how existing management and prevention measures may fail in a fundamental and critical guarantee in the accuracy and authenticity of on-site information, thereby limiting the effectiveness of dynamic risk assessment management. To address this issue of information assurance, a fire risk reduction framework that integrates the Fault Tree analysis method with blockchain technology has been proposed. This framework develops some smart contracts and leverages digital signature to maintain data authenticity and ensure data immutability, contributing toward tunnel fire risk reduction by revealing responsible parties and maintaining information-source integrity. Based on this framework, a tunnel fire risk reduction platform using blockchain technology has been developed and applied in a practical engineering case study. The results indicate that this platform promotes open sharing of risk information, facilitates accident liability tracing, and supports dynamic risk assessment, ultimately improving the efficiency of fire risk reduction in tunnel construction.
Keywords:
tunnel construction, fire risk, blockchain, responsibility tracing, risk reductionHow to Cite
Share
License
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Bucci, P., Kirschenbaum, J., Mangan, L. A., Aldemir, T., Smith, C., & Wood, T. (2008). Construction of event-tree/fault-tree models from a Markov approach to dynamic system reliability. Reliability Engineering and System Safety, 93(11), 1616–1627. https://doi.org/10.1016/j.ress.2008.01.008
Chen, J., Ma, X., Du, M., & Wang, Z. (2018). A blockchain application for medical information sharing. In 2018 IEEE International Symposium on Innovation and Entrepreneurship (TEMS-ISIE), Beijing, China. IEEE. https://doi.org/10.1109/TEMS-ISIE.2018.8478645
Cryptocurrency Monitoring Website. (2015). http://coinmarketcap.com/
Dinh, T. T. A., Wang, J., Chen, G., Liu, R., Ooi, B. C., & Tan, K.-L. (2017). BLOCKBENCH: A framework for analyzing private blockchains. In Proceedings of the ACM SIGMOD International Conference on Management of Data (Part F127746, pp. 1085–1100). https://doi.org/10.1145/3035918.3064033
Du, M., Chen, Q., Xiao, J., Yang, H., & Ma, X. (2020). Supply chain finance innovation using blockchain. IEEE Transactions on Engineering Management, 67(4), 1045–1058. https://doi.org/10.1109/TEM.2020.2971858
Fridolf, K., Nilsson, D., & Frantzich, H. (2013). Fire evacuation in underground transportation systems: A review of accidents and empirical research. Fire Technology, 49, 451–475. https://doi.org/10.1007/s10694-011-0217-x
Huang, H., Wu, C., Zhou, M., Chen, J., Han, T., & Zhang, L. (2024). Rock mass quality prediction on tunnel faces with incomplete multi-source dataset via tree-augmented naive Bayesian network. International Journal of Mining Science and Technology, 34(3), 323–337. https://doi.org/10.1016/j.ijmst.2024.03.003
Hyun, K. C., Min, S., Choi, H., Park, J., & Lee, I. M. (2015). Risk analysis using fault-tree analysis (FTA) and analytic hierarchy process (AHP) applicable to shield TBM tunnels. Tunnelling and Underground Space Technology, 49, 121–129. https://doi.org/10.1016/j.tust.2015.04.007
Kabir, S. (2017). An overview of fault tree analysis and its application in model-based dependability analysis. Expert Systems with Applications, 77, 114–135. https://doi.org/10.1016/j.eswa.2017.01.058
Li, Y. Z., & Ingason, H. (2018). Overview of research on fire safety in underground road and railway tunnels. Tunnelling and Underground Space Technology, 81, 568–589. https://doi.org/10.1016/j.tust.2018.08.013
Liao, S., Wang, W., & Xu, Z. (2010). Fire risk assessment model of long highway tunnels based on evidence theory. Journal of Railway Science and Engineering, 7(6), 80–85 (in Chinese).
Liu, Y., Yang, L., Piao, C., & Zhang, Z. (2021). Key technology research on blockchain-based railway engineering construction safety monitoring data sharing. Journal on Communications, 42(8), 206–216 (in Chinese).
Lu, W., Li, X., Xue, F., Zhao, R., Wu, L., & Yeh, A. G. O. (2021). Exploring smart construction objects as blockchain oracles in construction supply chain management. Automation in Construction, 129, Article 103816. https://doi.org/10.1016/j.autcon.2021.103816
Ministry of Housing and Urban-Rural Development of the People’s Republic of China. (2011). Risk management code for urban rail transit underground engineering construction (GB50652-2011).
Nakamoto, S. (2009). Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf
Ni, Y., Sun, B., & Wang, Y. (2021). Blockchain-based BIM digital project management mechanism research. IEEE Access, 9, 161342–161351. https://doi.org/10.1109/ACCESS.2021.3130270
Pan, X., Zhong, B., Shen, D., Yuan, X., & Wang, Y. (2022). Blockchain and deep learning technologies for construction equipment security information management. Automation in Construction, 136, Article 104186. https://doi.org/10.1016/j.autcon.2022.104186
Perera, S., Nanayakkara, S., Rodrigo, M. N. N., Senaratne, S., & Weinand, R. (2020). Blockchain technology: Is it hype or real in the construction industry?. Journal of Industrial Information Integration, 17, Article 100125. https://doi.org/10.1016/j.jii.2020.100125
Pradeep, A. S. E., Yiu, T. W., Zou, Y., & Amor, R. (2021). Blockchain-aided information exchange records for design liability control and improved security. Automation in Construction, 126, Article 103667. https://doi.org/10.1016/j.autcon.2021.103667
Reay, K. A., & Andrews, J. D. (2002). A fault tree analysis strategy using binary decision diagrams. Reliability Engineering & System Safety, 78(1), 45–56. https://doi.org/10.1016/S0951-8320(02)00107-2
Seike, M., Kawabata, N., & Hasegawa, M. (2016). Experiments of evacuation speed in smoke-filled tunnel. Tunnelling and Underground Space Technology, 53, 61–67. https://doi.org/10.1016/j.tust.2016.01.003
Sheng, D., Zhong, B., & Luo, H. (2021). Research on the framework of construction industry worker information management based on blockchain. Construction Economy, 42(10), 89–94 (in Chinese).
Shu, X., Yan, J., Hu, J., Wu, J., & Deng, B. (2020). Risk assessment model for building fires based on a Bayesian network. Journal of Tsinghua University (Science and Technology), 60(4), 321–327 (in Chinese).
Tian, Y., & Cai, J. (2011). Research on fire risk assessment method and software system for buildings. Journal of Applied Basic and Engineering Sciences, 19(1), 118–125.
Turk, Ž., & Klinc, R. (2017). Potentials of blockchain technology for construction management. Procedia Engineering, 196, 638–645. https://doi.org/10.1016/j.proeng.2017.08.052
Wang, Y., Huang, H., & Xue, Y. (2009). Risk analysis of tunnel collapse in drilling and blasting construction. Journal of Shenyang University of Architecture (Natural Science Edition), 25(1), 23–27 (in Chinese).
Wang, S., Lin, Z., & Yu, S. (2011). Characteristics and hazards of highway tunnel fire accidents. Fire Science and Technology, 30(4), 337–340.
Wang, S., Li, D., Zhang, Y., & Chen, J. (2019). Smart contract-based product traceability system in the supply chain scenario. IEEE Access, 7, 115122–115133. https://doi.org/10.1109/ACCESS.2019.2935873
Wang, Z., Wang, K., Wang, Y., & Wen, Z. (2022). A data management model for intelligent water project construction based on blockchain. Wireless Communications and Mobile Computing, 2022, Article 8482415. https://doi.org/10.1155/2022/8482415
Weng, T., & Liao, G. (2005). Discussion on the construction of expert software system for fire risk level assessment. China Safety Science Journal, (02), 40–43+2 (in Chinese).
World Economic Forum. (2016). Survey. http://www.coinfox.info/news/3184-world-economic-forum-survey-10-of-global-gdp-may-be-stored-with-blockchain-technology-by-2027
Wu, H., Zhong, B., Li, H., Guo, J., & Wang, Y. (2021). On-site construction quality inspection using blockchain and smart contracts. Journal of Management in Engineering, 37(6), Article 04021065. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000967
Wu, H., Zhong, B., Li, H., Chi, H.-L., & Wang, Y. (2022a). On-site safety inspection of tower cranes: A blockchain-enabled conceptual framework. Safety Science, 153, Article 105815. https://doi.org/10.1016/j.ssci.2022.105815
Wu, L., Lu, W., Zhao, R., Xu, J., Li, X., & Xuue, F. (2022b). Using blockchain to improve information sharing accuracy in the onsite assembly of modular construction. Journal of Management in Engineering, 38(3), Article 04022014. https://doi.org/10.1061/(ASCE)ME.1943-5479.0001029
Xu, Q., Chong, H.-Y., & Liao, P.-C. (2019). Collaborative information integration for construction safety monitoring. Automation in Construction, 102, 120–134. https://doi.org/10.1016/j.autcon.2019.02.004
Yan, Z., Yang, Q., & Zhu, H. (2005). Experimental study on temperature field distribution of fire in long and large highway tunnels. Journal of Southeast University (Natural Science Edition), 2005(S1), 84–88 (in Chinese).
Yang, Z. (2019). Research on deep integration of construction management and computer BIM technology. Journal of Advanced Computational Intelligence and Intelligent Informatics, 23(3), 379–384. https://doi.org/10.20965/jaciii.2019.p0379
Yang, Z., Wang, T., & Yang, K. (2021). Construction site information decentralized management using blockchain and smart contracts. Computer-Aided Civil and Infrastructure Engineering, 37(11), 1450–1467. https://doi.org/10.1111/mice.12804
Yuan, Y., & Wang, F. (2016). Current development and prospects of blockchain technology. Acta Automatica Sinica, 42(4), 481–494 (in Chinese).
Zhang, C., Qiao, M., Li, H., Chen, H., & Yang, Z. (2023). Research overview of blockchain technology application in the construction field. Journal of Railway Science and Engineering, 20(3), 1105–1115 (in Chinese).
Zhao, Y., & Fang, Z. (2007). Discussion on disaster prevention design of long and large traffic tunnels. Journal of Railway Engineering, (03), 40–44 (in Chinese).
Zhong, B., Guo, J., Zhang, L., Wu, H., Li, H., & Wang, Y. (2022). A blockchain-based framework for on-site construction environmental monitoring: Proof of concept. Building and Environment, 217, Article 109064. https://doi.org/10.1016/j.buildenv.2022.109064
Zhu, L., Liang, H., Tang, T., Xiao, C., & Xiao, X. (2022). Empowering railways with blockchain: prospects and case analysis. Journal of the China Railway Society, 44(9), 79–86 (in Chinese).
View article in other formats
CrossMark check
Published
Issue
Section
Copyright
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
License
This work is licensed under a Creative Commons Attribution 4.0 International License.