AN IOT-BASED EARTHQUAKE EARLY WARNING SYSTEM WITH FUZZY LOGIC FOR UTILITY CONTROL IN TEHRAN

Mahdi Akhavan, Pooria Rashvand, Mehran Seyed Razzaghi

Abstract


Introduction: In disaster scenarios, while predicting disasters is challenging, preparation is essential. Internet of Things (IoT) technology, which is well-established, can play a significant role in disaster management. For countries, especially those prone to seismic activity, implementing early warning systems is critical to saving lives and minimizing damage. These systems alert individuals and authorities when disasters strike. However, limited attention has been given to postdisaster decision-making for monitoring essential utilities, such as gas and electricity, during critical times. Methods: Integrating IoT with a Fuzzy system can improve decision-making after disasters, reducing costs and destruction in urban areas. Tehran, a city with high seismic risk and an extensive gas network, faces significant dangers from damage to gas and electricity systems in the event of a major earthquake. Results: The research highlights that the proposed IoT-Fuzzy system performs effectively when compared to the JICA Seismic Hazard Assessment of Tehran. It issues disconnection commands for critical utilities within 10 seconds based on predicted damage levels, helping to reduce secondary damage after an earthquake. This system shows promise in improving post-disaster response and safeguarding urban infrastructure.

Keywords


crisis management; internet of things; fuzzy system; early warning system; smart city; city management

Full Text:

PDF

References


Abdalzaher, M.S., Krichen M., Yiltas-Kaplan, D.; Dhaou, I. B.; Adoni, W.Y.H. (2023). Early Detection of Earthquakes Using IoT and Cloud Infrastructure: A Survey. Sustainability, Vol. 15, p. 11723. DOI: 10.3390/su151511713.

Ahn J. -K., Kim T. -H., and Koo H. (2024). Design for Optimized Public Safety and Earthquake Disaster Mitigation With IoT. IEEE Access, Vol. 12, pp. 43485-43494, DOI: 10.1109/ACCESS.2024.3379729.

Ahumada A., Altunkaynak A., Ayoub, A. (2015). Fuzzy logic-based attenuation relationships of strong motion earthquake records. Expert Systems With Applications, Vol. 42, Issue 3, pp. 1287–1297. DOI: 10.1016/j.eswa.2014.09.035.

Aki, K. and Richards, P. (2004). Quantitative Seismology, 2 University Science Books, Sausalit.

Atzori, L., Iera, A., and Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, Vol. 54, Issue 15, pp. 2787-2805. DOI: 10.1016/j.comnet.2010.05.010.

Azizzadeh, F., Babapour H., Akhavan, M., Azizzadeh, S., Khatoon V. D. T., and Hosseini, A. (2022). Expectations and Organizational Realities: The Relationship between Person and Organization. The International Journal of Interdisciplinary Organizational Studies, Vol. 17, Issue 1, pp. 23-34. DOI: 10.18848/2324-7649/CGP/v17i01/23-34.

Buzduga C., Graur A. , Ciufudean, C., and Vlad V. (2015). System for the detection earthquake victims construction and principle of operation. New Developments in Circuits, Systems, Signal Processing, Communications and Computers, pp. 110-115.

Chen, M., Miao, Y., Hao, Y., and Hwang, K. (2017). Narrow Band Internet of Things. IEEE Access, Vol. 5, pp. 20557-20577. DOI: 10.1109/access.2017.2751586.

Database, E. O. C. I. D. (2019). Total number of deaths as a result of natural disasters. [online] Available at: https://ourworldindata.org/natural-disasters [Date accessed April 25, 2024].

Doi, K. (2011). The operation and performance of Earthquake Early Warnings by the Japan Meteorological Agency. Soil Dynamics and Earthquake Engineering, Vol. 31, Issue 2, pp. 119-126. DOI: 10.1016/j.soildyn.2010.06.009.

Duhamel, C., Santos, A. C., Brasil, D., Châtelet, E., and Birregah, B. (2016). Connecting a population dynamic model with a multi-period location-allocation problem for post-disaster relief operations. Annals of Operations Research, Vol. 247, pp. 693-713. DOI: 10.1007/s10479-015-2104-1.

Erdik, M., Fahjan, Y., Ozel, O., Alcik, H., Mert, A., and Gul, M. (2003). Istanbul Earthquake Rapid Response and the Early Warning System. Bulletin of Earthquake Engineering, Vol. 1, pp. 157-163. DOI: 10.1023/A:1024813612271.

FEMA (1999) HAZUS Earthquake Loss Estimation Methodology. Technical Manual, Prepared by the National Ins- titute of Building Sciences for the Federal Emergency Management Agency, Washington DC.

Foghahaayeea H. N., Menhaj M. B., and Torbatib, H. M. (2014). Fuzzy decision support software for crisis management in gas transmission networks. Applied Soft Computing, Vol. 18, pp. 82-90. DOI: 10.1016/j.asoc.2014.01.019.

Fumio, Y. (2001). Seismic monitoring and early damage assessment systems in Japan. Progress in Structural Engineering and Materials, Vol. 3, Issue 1, pp. 66-75. DOI: 10.1002/pse.75.

Hoshiba, M., Iwakiri, K., Hayashimoto, N., Shimoyama, T., Hirano, K., Yamada, Y., Ishigaki, Y., and Kikuta, H. (2011). Outline of the 2011 off the Pacific coast of Tohoku Earthquake (Mw 9.0) — Earthquake Early Warning and observed seismic intensity. Earth, Planets and Space, Vol. 63, No 7. DOI: 10.5047/eps.2011.05.031.

Hoshiba, M. and Ozaki, T. (2014). Earthquake Early Warning and Tsunami Warning of the Japan Meteorological Agency, and Their Performance in the 2011 off the Pacific Coast of Tohoku Earthquake M9. In F. Wenzel & J. Zschau (Eds.), Early Warning for Geological Disasters: Scientific Methods and Current Practice, pp. 1-28. Springer Berlin Heidelberg. DOI: 10.1007/978-3-642-12233-0_1.

Jahanbakhshian, P., Akhavan, M., Rezapour, A., Ashrafi N. (2020). The relationship between organizational commitment and organizational performance with respect to knowledge sharing (Case study: Selected Project-based organizations). Turkish Journal of Computer and Mathematics Education (TURCOMAT), Vol. 12, Issue 13, pp. 4906-4916.

Jianshe, D., Shuning W., and Xiaoyin, Y. (1994). Computerized support systems for emergency decision making. Annals of Operations Research, Vol. 51, Issue 7, pp. 313-325. DOI: 10.1007/BF02048553.

JICA (2000). The study on seismic microzonation of the Greater Tehran Area in the Islamic Republic of Iran.

Lanzano G., Salzano E., Santucci de Magistris F., and Fabbrocino G. (2014). Seismic vulnerability of gas and liquid buried pipelines. Journal of Loss Prevention in the Process Industries, Vol. 28, pp. 72-78. DOI: 10.1016/j.jlp.2013.03.010.

Nord, J. H. , Koohang, A., and Paliszkiewiczc, J. (2019). The Internet of Things: Review and theoretical framework. Expert Systems With Applications, Vol. 133, pp. 97–108. DOI: 10.1016/j.eswa.2019.05.014.

Nokhbatolfoghahaayee H., Menhaj M. B., and Shafiee M. (2010). Fuzzy decision support system for crisis management with a new structure for decision making. Expert Systems with Applications, Vol. 37, Issue 5, pp. 3545–3552. DOI: 10.1016/j.eswa.2009.10.011.

Katayama, T. (2004). Earthquake disaster risk mitigation before and after the 1995 Kobe earthquake. 13th world conference on earthquake engineering, Vancouver, B.C., Canada, No. 5005.

Lee, E. K., Maheshwary, S., Mason, J., and Glisson, W. (2006). Decision support system for mass dispensing of medications for infectious disease outbreaks and bioterrorist attacks. Annals of Operations Research, Vol. 148, pp. 25-53. DOI: 10.1007/s10479-006-0087-7.

Maglogiannis, C.D.I. (2012). Bringing IoT and Cloud Computing towards Pervasive Healthcare. Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, Palermo, Italy, 2012, pp. 922-926. DOI: 10.1109/IMIS.2012.26.

Mali, J. R. and Kumbhar, M. S. (2016). Wireless Sensor Based Landslide Detection. International Journal of Latest Trends in Engineering and Technology, Vol. 7, Issue 1. DOI: 10.21172/1.71.066.

Manshoori, M.R. (2011). Evaluation of Seismic Vulnerability and Failure Modes for Pipelines. Procedia Engineering, Vol. 14, pp. 3042-3049. DOI: 10.1016/j.proeng.2011.07.383.

Mojarab M., Shahvar M. P., Poorveis M., Norozi N., and Asadi Z. (2017). Feasibility study of Tehran earthquake rapid earthquake warning network design. Managing environmental hazards, Vol. 4, Issue 1, pp. 63-81. DOI: 10.22059/jhsci.2017.63055.

Pierleoni P., Concetti R., Belli A., Palma L., Marzorati S., and Esposito M. (2023). A Cloud-IoT Architecture for Latency-Aware Localization in Earthquake Early Warning. Sensors, Vol. 23, Issue 20. DOI: 10.3390/s23208431.

Şen, Z. (2011). Supervised fuzzy logic modeling for building earthquake hazard assessment. Expert Systems With Applications, Vol. 38, Issue 12, pp. 14564–14573. DOI: 10.1016/j.eswa.2011.05.026.

Sharma K., Anand D., Sabharwal M., Tiwari P. K., Cheikhrouhou O., and Frikha T. (2021). A Disaster Management Framework Using Internet of Things-Based Interconnected Devices. Mathematical Problems in Engineering, Vol. 2021, Issue 1, p. 9916440. DOI: 10.1155/2021/9916440.

Sultanov K., Kumakov J., Loginov P., and Rikhsieva B. (2020). Strength of underground pipelines under seismic effects. Magazine of Civil Engineering, Vol. 93, pp. 97–120. DOI: 10.18720/MCE.93.9.

Raza U., Kulkarni P., and Sooriyabandara M. (2017). Low Power Wide Area Networks: An Overview. IEEE Communications Surveys & Tutorials, Vol. 19, No 2, pp. 855-873. DOI: 10.1109/COMST.2017.2652320.

Takaoka H., Hashimoto H., Ikematsu, S., and Hikida, M. (2006). Prediction Of Landslide-induced Debris Flow Hydrograph: The Atsumari Debris Flow Disaster In Japan. In: Monitoring, Simulation, Prevention and Remediation of Dense and Debris Flows. DOI: 10.2495/DEB060031.

Thoma, M., Meyer, S., Sperner, K., Meissner, S., Braun, T. (2012). On IoT-services: Survey, Classification and Enterprise Integration. 2012 IEEE International Conference on Green Computing and Communications, pp. 257-260. DOI 10.1109/GreenCom.2012.47.

Valizadeh, J., Ghahroudi, A.G., Soltani, S., Akhavan, M., Zaki, A., and Heravi, P. (2024). Mathematical modeling for the closed-loop supply chain with consideration of sustainability risks: a hybrid optimization approach. Environment, Development and Sustainability. DOI: 10.1007/s10668-023-04324-4.

Yanwei W., Xiaojun L., Zifa W., Jianping Sh., Enhe B. (2021). Deep learning for P-wave arrival picking in earthquake early warning. Earthquake engineering and engineering vibration, Vol. 20, pp. 391-402. DOI: 10.1007/s11803-021-2027-6.

Yeh, C.-H., Loh, C.-H., and Tsai, K.-C. (2006). Overview of Taiwan Earthquake Loss Estimation System. Natural Hazards, Vol. 37, pp. 23-37. DOI: 10.1007/s11069-005-4654-z.

Zadeh, L.A. (1965). Fuzzy sets. Information and Control, Vol. 8, Issue 3, pp. 338-353.

Zambrano, A. M., Perez, I., Palau, C., and Esteve, M. (2017). Technologies of Internet of Things applied to an Earthquake Early Warning System. Future Generation Computer Systems, Vol. 75, pp. 206-215. DOI: 10.1016/j.future.2016.10.009.

Zhou, H., Liu, B., and Wang, D. (2012). Design and Research of Urban Intelligent Transportation System Based on the Internet of Things. In: Wang, Y., Zhang, X. (eds) Internet of Things. Communications in Computer and Information Science, Vol 312. Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-32427-7_82.


Refbacks

  • There are currently no refbacks.




     

ISSN: 2500-0055