iTEVAC: an enhanced trusted evacuation system leveraging fog computing and IoT

References

• Al Shereiqi, I. M., & Sohail, M. M. (2020). Smart fire alarm system using IOT. Journal of Student Research, https://doi.org/10.47611/jsr.vi.882
   Google Scholar
• Al-Nabhan, N., Al-Aboody, N., & Alim Al Islam, A. B. M. (2019). A hybrid IoT-based approach for emergency evacuation. Computer Networks, 155, 87–97. https://doi.org/10.1016/j.comnet.2019.03.015
   Web of Science ®Google Scholar
• Araujo Lima, G. P., Viana Barbosa, J. D., Beal, V. E., Moret S. Gonçalves, M. A., Souza Machado, B. A., Gerber, J. Z., & Lazarus, B. S. (2021). Exploratory analysis of fire statistical data and prospective study applied to security and protection systems. International Journal of Disaster Risk Reduction, 61, 102308. https://doi.org/10.1016/j.ijdrr.2021.102308
   Web of Science ®Google Scholar
• Atila, U., Ortakci, Y., Ozacar, K., Demiral, E., & Karas, I. (2018). Smartescape: A mobile smart individual fire evacuation system based on 3D spatial model. ISPRS International Journal of Geo-Information, 7(6), 223. https://doi.org/10.3390/ijgi7060223
   Web of Science ®Google Scholar
• Bhawesh, C., & Gouthamkumar, N. (2020). Advanced integrated fire controlling system to reduce casualty and minimize deaths. In 2020 2nd international conference on advances in computing, communication control and networking (ICACCCN) (pp. 472–476). https://doi.org/10.1109/ICACCCN51052.2020.9362770
   Google Scholar
• Chen, A. Y., & Chu, J. C. (2016). Tdvrp and BIM integrated approach for in-building emergency rescue routing. Journal of Computing in Civil Engineering, 30(5), C4015003. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000522
   Web of Science ®Google Scholar
• Cheng, M.-Y., Chiu, K.-C., Hsieh, Y.-M., Yang, I.-T., & Chou, J.-S. (2016, July 21). Development of BIM-based real-time evacuation and rescue system for complex buildings. In 33th international symposium on automation and robotics in construction, Auburn, AL, USA. https://doi.org/10.22260/ISARC2016/0120.
   Google Scholar
• Cheng, M.-Y., Chiu, K.-C., Hsieh, Y.-M., Yang, I.-T., Chou, J.-S., & Wu, Y.-W. (2017). BIM integrated smart monitoring technique for building fire prevention and disaster relief. Automation in Construction, 84, 14–30. https://doi.org/10.1016/j.autcon.2017.08.027
   Web of Science ®Google Scholar
• Cheung, W.-F., Lin, T.-H., & Lin, Y.-C. (2018). A real-time construction safety monitoring system for hazardous gas integrating wireless sensor network and building information modeling technologies. Sensors, 18(2), 436. https://doi.org/10.3390/s18020436
   PubMed Web of Science ®Google Scholar
• Cortés-Pérez, J. P., Cortés-Pérez, A., & Prieto-Muriel, P. (2020). BIM-integrated management of occupational hazards in building construction and maintenance. Automation in Construction, 113, 103115. https://doi.org/10.1016/j.autcon.2020.103115
   Web of Science ®Google Scholar
• Deng, H., Ou, Z., Zhang, G., Deng, Y., & Tian, M. (2021). Bim and computer vision-based framework for fire emergency evacuation considering local safety performance. Sensors, 21(11), 3851. https://doi.org/10.3390/s21113851
   PubMed Web of Science ®Google Scholar
• Didar, N., & Abbaspour, M. (2023). Integrated evacuation and rescue management system in response to fire incidents. European Journal of Engineering and Technology Research, 8(1), 1–12. https://doi.org/10.24018/ejeng.2023.8.1.2946
   Google Scholar
• Fang, H., Lo, S., & Lo, J. T. Y. (2021). Building fire evacuation: An IoT-aided perspective in the 5G Era. Buildings, 11(12), 643. https://doi.org/10.3390/buildings11120643
   Web of Science ®Google Scholar
• Fu, M., & Liu, R. (2020). BIM-based automated determination of exit sign direction for intelligent building sign systems. Automation in Construction, 120, 103353. https://doi.org/10.1016/j.autcon.2020.103353
   Web of Science ®Google Scholar
• Gaur, A., Singh, A., Verma, A., & Kumar, A. (2022). Artificial intelligence and multi-sensor fusion based universal fire detection system for smart buildings using IoT techniques. IETE Journal of Research, 1–13. https://doi.org/10.1080/03772063.2022.2088626
   Web of Science ®Google Scholar
• Gelenbe, E., & Wu, F.-J. (2012). Large scale simulation for human evacuation and rescue. Computers & Mathematics with Applications, 64(12), 3869–3880. https://doi.org/10.1016/j.camwa.2012.03.056
   Web of Science ®Google Scholar
• Ibrahim, A. M., Venkat, I., Subramanian, K. G., Khader, A. T., & Wilde, P. D. (2016). Intelligent evacuation management systems: A review. ACM Transactions on Intelligent Systems and Technology, 7(3), 1–27. https://doi.org/10.1145/2842630
   Web of Science ®Google Scholar
• Immediately Dangerous To Life or Health (IDLH) Values. (n.d.). https://www.cdc.gov/niosh/idlh/intridl4.html
   Google Scholar
• Johnston, M. J., King, D., Arora, S., Behar, N., Athanasiou, T., Sevdalis, N., & Darzi, A. (2015). Smartphones let surgeons know WhatsApp: An analysis of communication in emergency surgical teams. The American Journal of Surgery, 209(1), 45–51. https://doi.org/10.1016/j.amjsurg.2014.08.030
   PubMed Web of Science ®Google Scholar
• Khan, A., Aesha, A. A., Aka, J. S., Rahman, S. M. F., & Rahman, M. J.-U. (2018). An IoT based intelligent fire evacuation system. In 2018 21st International conference of computer and information technology (ICCIT) (pp. 1–6). https://doi.org/10.1109/ICCITECHN.2018.8631945
   Google Scholar
• Kodali, R. K., & Yerroju, S. (2017). Iot based smart emergency response system for fire hazards. In 2017 3rd International conference on applied and theoretical computing and communication technology (iCATccT) (pp. 194–199). https://doi.org/10.1109/ICATCCT.2017.8389132
   Google Scholar
• Le, T. V., & Huan, T. T. (2020). Computational intelligence towards trusted cloudlet based Fog computing. In 2020 5th International conference on green technology and sustainable development (GTSD) (pp. 141–147). https://doi.org/10.1109/GTSD50082.2020.9303091
   Google Scholar
• Levin, S., Toerper, M., Hamrock, E., Hinson, J. S., Barnes, S., Gardner, H., Dugas, A., Linton, B., Kirsch, T., & Kelen, G. (2018). Machine-learning-based electronic triage more accurately differentiates patients with respect to clinical outcomes compared with the emergency severity index. Annals of Emergency Medicine, 71(5), 565–574.e2. https://doi.org/10.1016/j.annemergmed.2017.08.005
   PubMed Web of Science ®Google Scholar
• Li, B., Li, T., & Huang, D. (2018). Research on automatic fire monitoring and recognition technology based on digital image processing technology. In Proceedings of the 2018 8th International conference on management, education and information (MEICI 2018), Shenzang, People’s Republic of China. https://doi.org/10.2991/meici-18.2018.16
   Google Scholar
• Li, N., Becerik-Gerber, B., Krishnamachari, B., & Soibelman, L. (2014). A BIM centered indoor localization algorithm to support building fire emergency response operations. Automation in Construction, 42, 78–89. https://doi.org/10.1016/j.autcon.2014.02.019
   Web of Science ®Google Scholar
• Li, N., Yang, Z., Ghahramani, A., Becerik-Gerber, B., & Soibelman, L. (2014). Situational awareness for supporting building fire emergency response: Information needs, information sources, and implementation requirements. Fire Safety Journal, 63, 17–28. https://doi.org/10.1016/j.firesaf.2013.11.010
   Web of Science ®Google Scholar
• Lurz, F., Mueller, S., Lindner, S., Linz, S., Gardill, M., Weigel, R., & Koelpin, A. (2017). Smart communication and relative localization system for firefighters and rescuers. In 2017 IEEE MTT-S International microwave symposium (IMS) (pp. 1421–1424). https://doi.org/10.1109/MWSYM.2017.8058885
   Google Scholar
• Ma, G., & Wu, Z. (2020). BIM-based building fire emergency management: Combining building users’ behavior decisions. Automation in Construction, 109, 102975. https://doi.org/10.1016/j.autcon.2019.102975
   Web of Science ®Google Scholar
• Mahmud, R., Kotagiri, R., & Buyya, R. (2018). Fog computing: A taxonomy, survey and future directions (pp. 103–130). https://doi.org/10.1007/978-981-10-5861-5_5
   Google Scholar
• Mehra, S., & Tanmay. (2017). Disaster detection system using arduino. In 2017 International conference on information communication and embedded systems (ICICES) (pp. 1–6). https://doi.org/10.1109/ICICES.2017.8070777
   Google Scholar
• Mirahadi, F., McCabe, B., & Shahi, A. (2019). IFC-centric performance-based evaluation of building evacuations using fire dynamics simulation and agent-based modeling. Automation in Construction, 101, 1–16. https://doi.org/10.1016/j.autcon.2019.01.007
   Web of Science ®Google Scholar
• Mohammadiounotikandi, A., Fakhruldeen, H. F., Meqdad, M. N., Ibrahim, B. F., Jafari Navimipour, N., & Unal, M. (2023). A fire evacuation and control system in smart buildings based on the internet of things and a hybrid intelligent algorithm. Fire, 6(4), 171. https://doi.org/10.3390/fire6040171
   Google Scholar
• Nguyen, V.-Q., Vu, H.-T., Nguyen, V.-H., & Kim, K. (2022). A smart evacuation guidance system for large buildings. Electronics, 11(18), 2938. https://doi.org/10.3390/electronics11182938
   Web of Science ®Google Scholar
• Nikoloudakis, Y., Panagiotakis, S., Markakis, E., Pallis, E., Mastorakis, G., Mavromoustakis, C. X., & Dobre, C. (2016). A Fog-based emergency system for smart enhanced living environments. IEEE Cloud Computing, 3(6), 54–62. https://doi.org/10.1109/MCC.2016.118
   Web of Science ®Google Scholar
• Nowak, T., Hartmann, M., Troger, H.-M., Patino-Studencki, L., & Thielecke, J. (2017). Probabilistic multipath mitigation in RSSI-based direction-of-arrival estimation. In 2017 IEEE International conference on communications workshops (ICC workshops) (pp. 1024–1029). https://doi.org/10.1109/ICCW.2017.7962793
   Google Scholar
• Okokpujie, K., John, S. N., & Noma-Osaghae, E. (n.d.). A wireless sensor network based fire protection system with SMS alerts.
   Google Scholar
• Ortiz-Garcés, I., Andrade, R. O., Sanchez-Viteri, S., & Villegas-Ch, W. (2023). Prototype of an emergency response system using IoT in a Fog computing environment. Computers, 12(4), 81. https://doi.org/10.3390/computers12040081
   Web of Science ®Google Scholar
• OSHA Occupational Chemical Database-Documentation of the Threshold Limit Values (TLVs) and Biological Exposure Indices (BEIs)—Carbon Dioxide. (n.d.). https://www.osha.gov/chemicaldata/183
   Google Scholar
• Park, S., Park, S., Park, L., Park, S., Lee, S., Lee, T., Lee, S., Jang, H., Kim, S., Chang, H., & Park, S. (2018). Design and implementation of a smart IoT based building and town disaster management system in smart city infrastructure. Applied Sciences, 8(11), 2239. https://doi.org/10.3390/app8112239
   Google Scholar
• Raita, Y., Goto, T., Faridi, M. K., Brown, D. F. M., Camargo, C. A., & Hasegawa, K. (2019). Emergency department triage prediction of clinical outcomes using machine learning models. Critical Care, 23(1), 64. https://doi.org/10.1186/s13054-019-2351-7
   PubMedGoogle Scholar
• Rashid, K. M., Louis, J., & Fiawoyife, K. K. (2019). Wireless electric appliance control for smart buildings using indoor location tracking and BIM-based virtual environments. Automation in Construction, 101, 48–58. https://doi.org/10.1016/j.autcon.2019.01.005
   Web of Science ®Google Scholar
• Sahid, D., & Alaydrus, M. (2020). Multi sensor fire detection in low voltage electrical panel using modular fuzzy logic. In 2020 2nd International conference on broadband communications, wireless sensors and powering (BCWSP) (pp. 31–35). https://doi.org/10.1109/BCWSP50066.2020.9249400
   Google Scholar
• Sahil, & Sood, S. K. (2022). Fog-cloud centric IoT-based cyber physical framework for panic oriented disaster evacuation in smart cities. Earth Science Informatics, 15(3), 1449–1470. https://doi.org/10.1007/s12145-020-00481-6
   Web of Science ®Google Scholar
• Sloot, R. N. F., Heutink, A., & Voordijk, J. T. (2019). Assessing usefulness of 4D BIM tools in risk mitigation strategies. Automation in Construction, 106, 102881. https://doi.org/10.1016/j.autcon.2019.102881
   Web of Science ®Google Scholar
• Tang, Y., Xia, N., Lu, Y., Varga, L., Li, Q., Chen, G., & Luo, J. (2021). BIM-based safety design for emergency evacuation of metro stations. Automation in Construction, 123, 103511. https://doi.org/10.1016/j.autcon.2020.103511
   Web of Science ®Google Scholar
• Vinh, T. L., Thien, H. T., Huu, T. N., & Bouzefrane, S. (2023). TEVAC: Trusted evacuation system based Fog computing. In 2023 international conference on system science and engineering (ICSSE) (pp. 164–169). https://doi.org/10.1109/ICSSE58758.2023.10227231
   Google Scholar
• Wang, J., Wei, G., & Dong, X. (2021). A dynamic fire escape path planning method with BIM. Journal of Ambient Intelligence and Humanized Computing, 12(11), 10253–10265. https://doi.org/10.1007/s12652-020-02794-2
   Web of Science ®Google Scholar
• Wu, X., Zhang, X., Huang, X., Xiao, F., & Usmani, A. (2022). A real-time forecast of tunnel fire based on numerical database and artificial intelligence. Building Simulation, 15(4), 511–524. https://doi.org/10.1007/s12273-021-0775-x
   Web of Science ®Google Scholar
• Yousefpour, A., Fung, C., Nguyen, T., Kadiyala, K., Jalali, F., Niakanlahiji, A., Kong, J., & Jue, J. P. (2019). All one needs to know about Fog computing and related edge computing paradigms: A complete survey. Journal of Systems Architecture, 98, 289–330. https://doi.org/10.1016/j.sysarc.2019.02.009
   Web of Science ®Google Scholar
• Zualkernan, I. A., Aloul, F. A., Sakkia, V., Noman, H. A., Sowdagar, S., & Hammadi, O. A. (2019). An IoT-based emergency evacuation system. In 2019 IEEE International conference on internet of things and intelligence system (IoTaIS) (pp. 62–66). https://doi.org/10.1109/IoTaIS47347.2019.8980381
   Google Scholar