Urban Development Policy Making

Urban Development Policy Making

A Smart IoT-VR Framework for Designing Urban Flood Warning Systems

Document Type : Original Article

Authors
Ramtin Tavoosi Rad 1
Mohammad Ansari Ghojghar 2
1 Master Candidate, Department of Reclamation of arid and mountainous regions Engineering, Faculty of Natural Resources, University of Tehran, Karaj, Iran
2 Assistant Professor, Department of Reclamation of arid and mountainous regions Engineering, Faculty of Natural Resources, University of Tehran, Karaj, Iran
10.22034/judpm.2025.517126.1033
Abstract
Urban floods are among the most significant environmental, social, and economic natural hazards in urban watersheds. This research aims to explore the feasibility of utilizing cutting-edge Internet of Things (IoT) and Virtual Reality (VR) technologies for designing smart urban flood warning systems. Using a descriptive-analytical approach based on previous studies and library resources, this research analyzes the concept of urban flooding, flood warning systems, and the impact of IoT and VR on flood control. Flood warning systems play a crucial role in predicting and managing urban floods. IoT is employed for collecting, processing, and analysing large-scale environmental data and sharing the obtained information with other systems in a cloud-based shared environment.  VR can be used to materialize scenarios and simulate them to find optimal solutions. The results of this research indicate that the use of these technologies leads to increased prediction accuracy, reduced response time during crises and lower costsduring urban floods.
Keywords
Internet of Things (IoT)
Warning System
Integrated Management
Virtual Reality (VR)

Subjects

  1. Ahamed, J, Mou ,S , Chowdhury, T , Mannan, A , Mim, S , Tarannum, L and Noman ,T. AI-Driven Water Segmentation with deep learning models for Enhanced Flood Monitoring. 2024.
  2. Panggabean , F. Enhancing Flood Disaster Preparedness Through Virtual Reality: A VR-based Flood Simulator Game. Jurnal EMACS. 2023.Vol5.No2.69-72. DOI: 10.21512/emacsjournal.v5i2.9988.
  3. Aalami, M , Ardestani,M, Malekmohamadi,B. Flood Potential Modeling in Zarineh Rood Watershed Using Artificial Intelligence Models. Watershed Management Research. 2023. ISSN: 2981-2038. (Persian).
  4. Merz ,H , Kreibich, H , Schwarze,R and Thieken. A. Assesssment of economic flood damage. Natural Hazards and Earth System Sciences. 2010. 1697-1724. doi:10.5194/nhess-10-697-2010.
  5. Ansari Ghojghar, M, Pourmohammad, P. Assessment the impacts of Metaverse industry on flood modeling visualization. Journal of the Nivar. 2024.Vol. 48, No. 126-127. (Persian).
  6. Buttinger-Kreuzhuber ,A , Konev, A , Horvath, Z , Cornel ,D , Schwerdorf , i , Bloschl ,G and Waser, J. An integrated GPU-accelerated modeling framework for high-resolution simulations of rural and urban flash floods. Environmental.elsevier, Modelling and Software. 2022.105480. https://doi.org/10.1016/j.envsoft.2022.105480 .
  7. Wan Mohtar,M , Wan Hanna, M, Jazuri, A, Khairul ,N , Abdul Maulud and Nur Shazwani ,M. Urban flash flood index based on historical rainfall events. Elsevier, Sustainable Cities and Society. 2020.Volume 56. https://doi.org/10.1016/j.scs.2020.102088.
  8. Nkwunonwo, U.C , Whitworth,M and Baily, B. A review of the current status of flood modelling for urban flood risk management in the developing countries. elsevier, Scientific African. 2020. 2468-2276. https://doi.org/10.1016/j.sciaf.2020.e00269.
  9. Ebrahimi heravi,B , Rangzan, K and Kabolizadeh, M. Comparing Methods of Artificial Neural Network and Fuzzy System in Determining Pre-flooding Warning (Case Study: Zard River Sub-basin- Khuzestan Province). Geography and Environmental Planning. 2016. 28-65-1. (Persian).
  10. Aljohani, F , Abi Sen, A , Ramazan ,M , Alzahrani, B and Bahbouh, N. A Smart Framework for Managing Natural Disasters Based on the IoT and ML. Applied Science. 2023.13,3888 https://doi.org/10.3390/app13063888.
  11. Amirebrahimi, S , Rajabifard, A , Mendis, P and Ngo, T. A framework for a microscale flood damage assessment and visualization for a building using BIM–GIS integration. International Journal of Digital Earth. 2016. ISSN: 1753-8947 1753-8955. https://doi.org/10.1080/17538947.2015.1034201
  12. Chang, Li , Chang, F , Yang, S , Kao, I , Ku, Y , Kuo, C and Mat Amin Ir, M. Building an Intelligent Hydroinformatics Integration Platform for Regional Flood Inundation Warning Systems. Water journal. 2019. 11,9. doi:10.3390/w11010009.
  13. Hsieh, Sh , Chang, D , Yang, S , Wang, H and Yeh, K. Artificial Intelligence Methodologies Applied toPrompt Pluvial Flood Estimation and Prediction.Water journal. 2020.12, 3552. doi:10.3390/w12123552.
  14. Samadi, S. The convergence of AI, IoT, and big data for advancing flood analytics research.Forntiers. 2022. DOI 10.3389/frwa.2022.786040.
  15. Okeke Remigius ,O and Ehikhamenle, M. Design Analysis of an IoT based Early Flood Detection and Alerting System. International Journal of Advanced Engineering Research and Science (IJAERS). 2024. Vol-11, Issue-2. Article DOI: https://dx.doi.org/10.22161/ijaers.112.7.
  16. Mirzababaei, M and Pouresmaiil, H. Metaverse, Challenges and requirements for development and deployment. Islamic Consultative Assembly Research Center. 2024. 310.19380 (Persian)
  17. Schiavini ,R and Meurer ,H. USING VIRTUAL REALITY TO THE SAFETY WARNINGS DESIGN: THE EFFICIENCY THROUGH PRESENCE. Revista Conhecimento Online. 2021. a:13, Vol23:2,21-45.DOI: https://doi.org/10.25112/rco.v2i0.2535.
  18. Donratanapat, N , Samadi, S , Vidal, M. J and Sadeghi Tabas,S. A national-scale big data prototype for real-time flood emergency response and management. Environ. Model. Softw. 2020. 133, 104828. doi: 10.1016/j.envsoft.2020.104828.
  19. Binti Yahaya ,N and Binti Mat Zain,N. SIMULATING FLOOD DISASTER USING AUGMENTED REALITY APPLICATION. Progress In computing and Mathematics journal(PCMJ). 2024. Vol1.
  20. U.S. DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration National Weather Service. Flood Warning Systems Manual. NOAA’s National Weather Service. 2012.
  21. Javaheri, N. Performance evaluation of the basin flood warning system in flood. National Committee of Large Dams of Iran. (Specialized committees for the operation, maintenance and rehabilitation of dams and dams for hydroelectric power plants). 2014. (Persian)
  22. Petrillo, A , De Felice , F , De Luca, C and Di Chiara , S. Physical and digital worlds: implications and opportunities of the metaverse.Elsevier, Procedia Computer Science. 2023.217. 1744-1754.
  23. Rafiei, M. Identification and Prioritization of Metaverse Infrastructure with a Fuzzy Approach. Metaverse & Virtual Transformation. The International Journal of Metaverse & Virtual Transformation (IJMVT). 2024. 1(1): 1-9.
  24. Urbas, m , Cok ,V and Vlah ,D .VR as a 3D Modelling Tool in Engineering Design Applications. Applied Sciences. 2021. 11,7570. https://doi.org/10.3390/app11167570
  25. Lim,D , Meyers,P , Quick,M , Rudlosky,S , Lee,E , Schwelling,E and Varshn,A. Weather Forecasting in Virtual Reality. NOAA/NESDIS/STAR . 2019.
  26. Li ,M , Banerjee ,N and Banerjee, S. Using Motion Forecasting for Behavior-Based Virtual Reality (VR) Authentication. 2024. arXiv:2401.16649v1.
  27. Ooi, S , Tanimoto, T and Sano, M. Virtual reality fire disaster training system for improving disaster awareness. In Proceedings of the 8th International Conference on Educational and Information Technology. 2019. pp. 301-307. https://doi.org/10.1145/3318396.3318431
  28. Sermet, Y and Demir, I. Flood action VR: a virtual reality framework for disaster awareness and emergency response training. 2019. In ACM SIGGRAPH 2019 Posters, 27, pp. 1-2. https://doi.org/10.1145/3306214.3338550
  29. Liang,H , Burgess,L ,Liao, W ,Blasch,E and Yu, W. Deep Learning Assist to IoT Eearch Engine for Disaster Damage Assesment. Cyber-Phisical Systems. 2022.
  30. Ibarreche,J , Aquino,R , Edwards,R.M , Rangel,V Perez,I and Martinez,M. Flash Flood Early Warning System in Colima Mexico. Sensors. 2020. 20(18), 5231.
  31. Ghanbari,A , Tahmasebipour,N , Zeinivand,H , AliHeidari,M and Bdollahi,S. Flood Warning System Using Internet of Things, Artificial Intelligence and Hydraulic Modeling (Case study: Behesht-Abad Watershed, Iran). Springer, Acta Geophizika. 2023. Vol72, 2815-2829.
  32. Jang, B and Jung ,I. Develompent of Hig-Precision Urban Flood-Monitoring Technology for Sustainable Smart Cities. Seonsors. 2023. https://doi.org/ 10.3390/ s23229167.
  33. Duarte, E , Rebelo ,F and Wogalter ,M. Virtual Reality and Its Potential for Evaluating Warning Compliance.  Human Factors and Ergonomics in Manufacturing. 2010. 20 (6) 526–537.
  34. Gamberini,L , Batelli,A , Benvegnu,G , Orso, V , Spagnolli, A and Ferri, M. Designing"Safer Water." A Virtual Reality Tool for the Safety and the Psychological Well-Being of Citizens Exposed to the Risk of Natural Disasters. Human-Media Interaction. 2021.Vol12. https://doi.org/10.3389/fpsyg.2021.674171
  35. Alizadeh , B and sakib, M. Immersive Virtual Reality to Measure Flood Risk Perception in Urban Environments. Confrence Paper. 2023.
Urban Development Policy Making
Volume 2, Issue 2
Summer 2025
Pages 231-245

  • Receive Date 13 February 2025
  • Revise Date 19 March 2025
  • Accept Date 11 April 2025
  • Publish Date 10 May 2025