Published March 16, 2026 | Version v1
Book chapter Open

Smart cities in the context of climate change and disaster risk: A bibliometric and literature review.

Authors/Creators

  • 1. PhD Student, Gazi University, Institute of Science, Department of Architecture, Ankara-Türkiye. duygusavur92@gmail.com
  • 2. Prof. Dr., Gazi University, Faculty of Architecture, Department of Architecture, Ankara-Türkiye. asenad@gazi.edu.tr

Contributors

Description

Population patterns have shifted steadily since the Industrial Revolution, as more people migrated from rural areas to urban areas (Lee et al., 2023). This imbalance caused by humans has brought many problems with it. One of these is ecological degradation resulting from the uncontrolled use of resources. The increase in raw material consumption also causes an increase in energy consumption. These have a domino effect on the world. The construction sector, one of the main focuses of this article, also plays a key role in energy consumption. According to statistics, the construction sector consumes 30% of global energy consumption and more than 50% of electricity worldwide (Santamouris & Vasilakopoulou, 2021). In consequence of the rapid increase in ecological degradation, the effects of climate change have begun to be felt more globally. In addition to the uncontrolled use of natural resources, the negative effects of non-renewable energy sources on the atmosphere have triggered a series of emergency signals on Earth. Although these signals manifest themselves separately in the air, on land, and in water, every component on Earth has been individually affected by the consequences of climate change, which is the largest domino at the top of the pile.

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Additional details

Identifiers

ISBN
979-10-7023-053-4

Dates

Issued
2026-04-24

References

  • Abdeen, F. N., Fernando, T., Kulatunga, U., Hettige, S., & Ranasinghe, K. D. A. (2021). Challenges in multi-agency collaboration in disaster management: A Sri Lankan perspective. International Journal of Disaster Risk Reduction, 62, 102399. https://doi.org/10.1016/j.ijdrr.2021.102399
  • Abokyi, E., Appiah-Konadu, P., Abokyi, F., & Oteng-Abayie, E. F. (2019). Industrial growth and emissions of CO2 in Ghana: The role of financial development and fossil fuel consumption. Energy Reports, 5, 1339–1353. https://doi.org/10.1016/j.egyr.2019.09.002
  • Afrin, S., Chowdhury, F. J., & Rahman, Md. M. (2021). COVID-19 Pandemic: Rethinking strategies for resilient urban design, perceptions, and planning. Frontiers In Sustainable Cities, 3, 668263. https://doi.org/10.3389/ frsc.2021.668263
  • Agarwal, Y., Balaji, B., Gupta, R., Lyles, J., Wei, M., & Weng, T. (2010). Occupancy-driven energy management for smart building automation. Proceedings of The 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency In Building, 1–6. https://doi. org/10.1145/1878431.1878433
  • Alam, M. R., Reaz, M. B. I., & Ali, M. A. M. (2012). A review of smart homes—Past, present, and future. IEEE Transactions on Systems, man, and cybernetics, part C (applications and reviews), 42(6), 1190–1203. https://doi. org/10.1109/tsmcc.2012.2189204
  • Alexander, L. V., & Herold, N. (2016). Climpact2 User Guide. World Meteorological Organization. https://github.com/arccss-extremes/climpact2/
  • Aliero, M. S., Asif, M., Ghani, I., Pasha, M. F., & Jeong, S. R. (2022). Systematic review analysis on smart building: Challenges and opportunities. Sustainability, 14(5), 3009. https://doi.org/10.3390/su14053009
  • Almalaq, A., Hao, J., Zhang, J. J., & Wang, F.Y. (2019). Parallel Building: A complex system approach for smart building energy management. IEEE/ CAA Journal of Automatica Sinica, 6(6), 1452–1461. https://doi.org/10.1109/ jas.2019.1911768
  • Almulhim, A. I., & Cobbinah, P. B. (2024). Framing resilience in Saudi Arabian Cities: On climate change and urban policy. Sustainable Cities and Society, 101, 105172. https://doi.org/10.1016/j.scs.2024.105172
  • Ameur, H. B., Han, X., Liu, Z., & Peillex, J. (2022). When did global warming start? A new baseline for carbon budgeting. Economic Modelling, 116, 106005. https://doi.org/10.1016/j.econmod.2022.106005
  • Aria, M., & Cuccurullo, C. (2025). Biblioshiny (Version v.5.1.1) [Computer software]. Retrieved December, 2, 2025 from https://www.bibliometrix.org
  • Aslan, E., & Özüpak, Y. (2025). Detection of road extraction from satellite images with deep learning method. Cluster Computing, 28(1), 72. https://doi. org/10.1007/s10586-024-04880-y
  • Balaji, B., Bhattacharya, A., Fierro, G., Gao, J., Gluck, J., Hong, D., Johansen, A., Koh, J., Ploennigs, J., Agarwal, Y., Bergés, M., Culler, D., Gupta, R. K., Kjærgaard, M. B., Srivastava, M., & Whitehouse, K. (2018). Brick: Metadata schema for portable smart building applications. Applied Energy, 226, 1273–1292. https://doi.org/10.1016/j.apenergy.2018.02.091
  • Balta-Ozkan, N., Amerighi, O., & Boteler, B. (2014). A comparison of consumer perceptions towards smart homes in the UK, Germany and Italy: Reflections for policy and future research. Technology Analysis & Strategic Management, 226 1176–1195. https://doi.org/10.1080/09537325.2014.975788
  • Berglund, E. Z., Monroe, J. G., Ahmed, I., Noghabaei, M., Do, J., Pesantez, J. E., Khaksar Fasaee, M. A., Bardaka, E., Han, K., Proestos, G. T., & Levis, J. (2020). Smart infrastructure: A vision for the role of the civil engineering profession in smart cities. Journal of Infrastructure Systems, 26(2), 03120001. https://doi.org/10.1061/(asce)is.1943-555x.0000549
  • Bilgili, M., Tumse, S., & Nar, S. (2024). Comprehensive overview on the present state and evolution of global warming, climate change, Greenhouse gasses and renewable energy. Arabian Journal for Science and Engineering, 49(11), 14503–14531. https://doi.org/10.1007/S13369-024-09390-Y
  • Brazzola, N., Patt, A., & Wohland, J. (2022). Definitions and implications of climate-neutral aviation. Nature Climate Change, 12(8), 761–767. https://doi. org/10.1038/s41558-022-01404-7
  • Caragliu, A., Del Bo, C. F., & Nijkamp, P. (2023). "Smart cities in Europe" revisited: A meta-analysis of smart city economic impacts. Journal of Urban Technology, 30(4), 51–69. https://doi.org/10.1080/10630732.2023.2220136
  • Chan, M., Estève, D., Escriba, C., & Campo, E. (2008). A review of smart homes—Present state and future challenges. Computer Methods and Programs in Biomedicine, 91(1), 55–81. https://doi.org/10.1016/j.cmpb.2008.02.001
  • Chasta, R., Singh, R., Gehlot, A., Mishra, R. G., & Choudhury, S. (2016). A smart building automation system. International Journal of Smart Home, 10(8), 91–98. https://doi.org/10.14257/Ijsh.2016.10.8.10
  • Chen, C. (2017). Science mapping: A systematic review of the literature. Journal of Data and Information Science, 2(2), 1–40. https://doi.org/10.1515/ jdis-2017-0006
  • Chen, H., Chou, P., Duri, S., Lei, H., & Reason, J. (2009). The design and implementation of a smart building control system. In 2009 IEEE International Conference on e-Business Engineering (pp. 255-262). IEEE.
  • Chevallier, Z., Finance, B., & Boulakia, B. C. (2020). A reference architecture for smart building digital twin. In R. Garcia-Castro, J. Davies, G. Antoniou, & F. C. (Eds.), Proceedings of the 2020 International Workshop on Semantic Digital Twins (SeDiT 2020) (Vol. 2615). CEUR Workshop Proceedings. https://ceur-ws.org/Vol-2615/paper2.pdf
  • Clarivate. (2025). Web of Science Core Collection. Retrieved December, 2, 2025 from https://www.webofscience.com/wos/woscc/smart-search
  • Cortese, T. T. P., Almeida, J. F. S. D, Batista, G. Q., Storopoli, J. E., Liu, A., & Yigitcanlar, T. (2022). Understanding sustainable energy in the context of smart cities: A PRISMA review. Energies, 15(7), 2382. https://doi.org/10.3390/ en15072382
  • Dang, T. Q., Tran, B. H., Le, Q. N., Tanim, A. H., Bui, V. H., Mai, S. T., Thanh, P. N., & Anh, D. T. (2025). Integrating intelligent hydro-informatics into an effective early warning system for risk-informed urban flood management. Environmental Modelling & Software, 183, 106246. https://doi.org/10.1016/j. envsoft.2024.106246
  • Darko, A., Chan, A. P. C., Adabre, M. A., Edwards, D. J., Hosseini, M. R., & Ameyaw, E. E. (2020). Artificial intelligence in the AEC Industry: Scientometric analysis and visualization of research activities. Automation In Construction, 112, 103081. https://doi.org/10.1016/j.autcon.2020.103081
  • Daud, S. M. S. M., Yusof, M. Y. P. M., Heo, C. C., Khoo, L. S., Singh, M. K. C., Mahmood, M. S., & Nawawi, H. (2022). Applications of drone in disaster management: A scoping review. Science & Justice, 62(1), 30-42.
  • De Silva, L. C., Morikawa, C., & Petra, I. M. (2012). State of the art of smart homes. Engineering Applications of Artificial Intelligence, 25(7), 1313– 1321. https://doi.org/10.1016/j.engappai.2012.05.002
  • Ding, X., Du, W., & Cerpa, A. (2019). OCTOPUS: Deep reinforcement learning for holistic smart building control. Proceedings of The 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, 326–335. https://doi.org/10.1145/3360322.3360857
  • Djenouri, D., Laidi, R., Djenouri, Y., & Balasingham, I. (2019). Machine learning for smart building applications: Review and taxonomy. ACM Computing Surveys, 52(2), 1–36. https://doi.org/10.1145/3311950
  • Dong, B., Prakash, V., Feng, F., & O'Neill, Z. (2019). A review of smart building sensing system for better indoor environment control. Energy and Buildings, 199, 29–46. https://doi.org/10.1016/j.enbuild.2019.06.025
  • Edirisinghe, R., & Woo, J. (2021). BIM-Based Performance monitoring for smart building management. Facilities, 39(1/2), 19–35. https://doi. org/10.1108/f-11-2019-0120
  • Eini, R., Linkous, L., Zohrabi, N., & Abdelwahed, S. (2021). Smart building management system: Performance specifications and design requirements. Journal of Building Engineering, 39, 102222. https://doi.org/10.1016/j. jobe.2021.102222
  • Elvas, L. B., Mataloto, B. M., Martins, A. L., & Ferreira, J. C. (2021). Disaster management in smart cities. Smart Cities, 4(2), 819–839. https://doi. org/10.3390/smartcities4020042
  • Emekci, S. (2022). From smart homes to smart cities: How smart homes contribute to the sustainable development goals. In A. C. Pego (Ed.), Advances In Public Policy and Administration (Pp. 321–337). IGI Global. https://doi. org/10.4018/978-1-7998-7785-1.ch018
  • Farzaneh, H., Malehmirchegini, L., Bejan, A., Afolabi, T., Mulumba, A., & Daka, P. P. (2021). Artificial intelligence evolution in smart buildings for energy efficiency. Applied Sciences, 11(2), 763. https://doi.org/10.3390/app11020763
  • Gracias, J. S., Parnell, G. S., Specking, E., Pohl, E. A., & Buchanan, R. (2023). Smart cities—a structured literature review. Smart Cities, 6(4), 1719– 1743. https://doi.org/10.3390/smartcities6040080
  • Graveline, M. H., & Germain, D. (2022). Disaster risk resilience: conceptual evolution, key issues, and opportunities. International Journal of Disaster Risk Science, 13(3), 330–341. https://doi.org/10.1007/S13753-022-00419-0
  • Gunatilaka, R. N., Abdeen, F. N., & Sepasgozar, S. M. E. (2021). Developing a scoring system to evaluate the level of smartness in commercial buildings: A case of Sri Lanka. Buildings, 11(12), 644. https://doi.org/10.3390/ buildings11120644
  • Harper, R. (Ed.). (2003). Inside the smart home. Springer Science & Business Media.
  • Huotari, M., Malhi, A., & Främling, K. (2024). Machine learning applications for smart building energy utilization: A Survey: M. Huotari. Archives of Computational Methods In Engineering, 31(5), 2537–2556. https:// doi.org/10.1007/S11831-023-10054-7
  • Hurlimann, A. C., Moosavi, S., & Browne, G. R. (2021). Climate change transformation: A definition and typology to guide decision making in urban environments. Sustainable Cities and Society, 70, 102890. https://doi. org/10.1016/j.scs.2021.102890
  • Hurtado, L. A., Nguyen, P. H., & Kling, W. L. (2015). Smart grid and smart building inter-operation using agent-based particle swarm optimization. Sustainable Energy, Grids and Networks, 2, 32–40. https://doi.org/10.1016/j. segan.2015.03.003
  • Huseien, G. F., & Shah, K. W. (2022). A review on 5G technology for smart energy management and smart buildings in Singapore. Energy and AI, 7, 100116. https://doi.org/10.1016/j.egyai.2021.100116
  • Ince, A. T., Elma, O., Selamoğulları, U. S., & Vural, B. (2014). Data reliability and latency test for ZigBee-based smart home energy management systems. In 7th International Ege Energy Symposium an Exhibition, Usak, Turkey (pp. 1-8).
  • Jang, Y. H., Park, S. I., Kwon, T. H., & Lee, S. H. (2021). CityGML urban model generation using national public datasets for flood damage simulations: A case study in Korea. Journal of Environmental Management, 297, 113236. https://doi.org/10.1016/j.jenvman.2021.113236
  • Janssen, M., Lee, J., Bharosa, N., & Cresswell, A. (2010). Advances in multi-agency disaster management: Key elements in disaster research. Information Systems Frontiers, 12(1), 1–7. https://doi.org/10.1007/S10796- 009-9176-x
  • Jia, R., Jin, B., Jin, M., Zhou, Y., Konstantakopoulos, I. C., Zou, H., Kim, J., Li, D., Gu, W., Arghandeh, R., Nuzzo, P., Schiavon, S., Sangiovanni- Vincentelli, A. L., & Spanos, C. J. (2018). Design automation for smart building systems. Proceedings of The IEEE, 106(9), 1680–1699. https://doi.org/10.1109/ jproc.2018.2856932
  • Josipovic, N., & Viergutz, K. (2023). Smart solutions for municipal flood management: Overview of literature, trends, and applications in German Cities. Smart Cities, 6(2), 944–964. https://doi.org/10.3390/smartcities6020046
  • Kawyitri, N., & Shekhar, A. (2021). Assessing vulnerability and capacity of bhubaneswar as a progressive smart-city: An empirical case study of Fani Cyclone impact on the city. International Journal of Disaster Risk Reduction, 56, 101986. https://doi.org/10.1016/j.ijdrr.2020.101986
  • Keles, C., Karabiber, A., Akcin, M., Kaygusuz, A., Alagoz, B. B., & Gul, O. (2015). A smart building power management concept: Smart socket applications with DC distribution. International Journal of Electrical Power & Energy Systems, 64, 679–688. https://doi.org/10.1016/j.ijepes.2014.07.075
  • Kermani, M., Adelmanesh, B., Shirdare, E., Sima, C. A., Carn, D. L., & Martirano, L. (2021). Intelligent energy management based on SCADA system in a real microgrid for smart building applications. Renewable Energy, 171, 1115–1127. https://doi.org/10.1016/j.renene.2021.03.008
  • Keshavarzi, G., Yıldırım, Y., & Arefi, M. (2021). Does scale matter? An overview of the "smart cities" literature. Sustainable Cities and Society, 74, 103151. https://doi.org/10.1016/j.scs.2021.103151
  • Khan, S. M., Shafi, I., Butt, W. H., Diez, I. D. L. T., Flores, M. A. L., Galn, J. C., & Ashraf, I. (2023). A Systematic review of disaster management systems: Approaches, challenges, and future directions. Land, 12(8), 1514. https://doi. org/10.3390/land12081514
  • Khatibi, H., Wilkinson, S., Sweya, L. N., Baghersad, M., & Dianat, H. (2024). Navigating climate change challenges through smart resilient cities: A comprehensive assessment framework. Land, 13(3), 266. https://doi. org/10.3390/land13030266
  • Khurshudov, A. (2024). On defining smart cities using transformer neural networks. International Journal of Computers & Technology, 24, 14–29. https:// doi.org/10.24297/ijct.v24i.9579
  • Kim, D., Yoon, Y., Lee, J., Mago, P. J., Lee, K., & Cho, H. (2022). Design and implementation of smart buildings: A review of current research trend. Energies, 15(12), 4278. https://doi.org/10.3390/en15124278
  • Kitchin, R. (2022). Conceptualising smart cities. Urban Research & Practice, 15(1), 155–159. https://doi.org/10.1080/17535069.2022.2031143
  • Koutsoyiannis, D. (2021). Rethinking climate, climate change, and their relationship with water. Water, 13(6), 849. https://doi.org/10.3390/w13060849
  • Kumar, P., Barat, A., Sarthi, P. P., & Raj, V. (2025). Assessment of future urban precipitation extremes over smart cities of the gangetic plains using statistically downscaled CMIP6 projections. Modeling Earth Systems and Environment, 11(4), 267. https://doi.org/10.1007/s40808-025-02459-z
  • Kumaş, E., & Aslan, D. (2025). A case study: Making decisions for sustainable University Campus planning using GeoAI. International Journal of Engineering and Geosciences, 10(1), 22–35. https://doi.org/10.26833/ ijeg.1506265
  • Latifah, A., Supangkat, S. H., & Ramelan, A. (2020). Smart building: A literature review. 2020 International Conference on ICT For Smart Society (ICISS), 1–6. IEEE. https://doi.org/10.1109/iciss50791.2020.9307552
  • Lee, H., Calvin, K., Dasgupta, D., Krinner, G., Mukherji, A., Thorne, P., Trisos, C., Romero, J., Aldunce, P., Barrett, K., and Jotzo, F. (2023). IPCC, 2023: Climate Change 2023: Synthesis Report: A Report of the Intergovernmental Panel on Climate Change. Intergovernmental Panel on Climate Change.
  • Lnenicka, M., Nikiforova, A., Luterek, M., Azeroual, O., Ukpabi, D., Valtenbergs, V., & Machova, R. (2022). Transparency of open data ecosystems in smart cities: Definition and assessment of the maturity of transparency in 22 smart cities. Sustainable Cities and Society, 82, 103906. https://doi. org/10.1016/j.scs.2022.103906
  • Lokshina, I. V., Greguš, M., & Thomas, W. L. (2019). Application of integrated building information modeling, Iot and blockchain technologies in system design of a smart building. Procedia Computer Science, 160, 497–502. https://doi.org/10.1016/j.procs.2019.11.058
  • Luca, O., Gaman, F., & Răuță, E. (2021). Towards a national harmonized framework for urban plans and strategies in Romania. Sustainability, 13(4), 1930. https://doi.org/10.3390/su13041930
  • Lutolf, R. (1992). Smart home concept and the integration of energy meters into a home based system. Seventh International Conference On Metering Apparatus And Tariffs For Electricity Supply 1992, 277–278. https://ieeexplore. ieee.org/abstract/document/187310
  • Martins, F., Patro, C., Moura, P., & De Almeida, A. T. (2021). A review of energy modeling tools for energy efficiency in smart cities. Smart Cities, 4(4), 1420–1436. https://doi.org/10.3390/smartcities4040075
  • Mashwani, Z. U. R. (2020). Environment, climate change and biodiversity. In S. Fahad et al. (Eds.), Environment, climate, plant and vegetation growth (pp. 473–501). Springer. https://doi.org/10.1007/978-3-030-49732-3_19
  • Mills, B. J. W., Krause, A. J., Scotese, C. R., Hill, D. J., Shields, G. A., & Lenton, T. M. (2019). Modelling the long-term carbon cycle, atmospheric CO2, and earth surface temperature from late Neoproterozoic to present day. Gondwana Research, 67, 172–186. https://doi.org/10.1016/j.gr.2018.12.001
  • Monroe, R. The Keeling Curve. The Keeling Curve. Retrieved 11 November 2025, from https://keelingcurve.ucsd.edu
  • Motta, M., De Castro Neto, M., & Sarmento, P. (2021). A mixed approach for urban flood prediction using machine learning and GIS. International Journal of Disaster Risk Reduction, 56, 102154. https://doi.org/10.1016/j. ijdrr.2021.102154
  • Namavar, M., Moghaddam, M. R. A., & Shafiei, M. (2023). Developing an indicator-based assessment framework for assessing the sustainability of urban water management. Sustainable Production and Consumption, 40, 1–12. https://doi.org/10.1016/j.spc.2023.06.006
  • Nguyen, D. N., Usuda, Y., & Imamura, F. (2024). Gaps in and opportunities for disaster risk reduction in urban areas through international standardization of smart community infrastructure. Sustainability, 16(21), 9586. https://doi. org/10.3390/su16219586
  • Nunes, L. J. R. (2023). The rising threat of atmospheric CO2: A review on the causes, impacts, and mitigation strategies. Environments, 10(4), 66. https:// doi.org/10.3390/environments10040066
  • Obringer, R., & Nateghi, R. (2021). What makes a city 'smart' in the anthropocene? A critical review of smart cities under climate change. Sustainable Cities and Society, 75, 103278. https://doi.org/10.1016/j.scs.2021.103278
  • Oliveira, L. F., Oliveira, D., & Frota, Y. (2023). Defining routes for emergency response from climate events: A data-oriented approach. IEEE Latin America Transactions, 21(10), 1064–1072. https://doi.org/10.1109/ tla.2023.10255445
  • Pardamean, B., Muljo, H. H., Cenggoro, T. W., Chandra, B. J., & Rahutomo, R. (2019). Using transfer learning for smart building management system. Journal of Big Data, 6(1), 110. https://doi.org/10.1186/S40537-019-0272-6
  • Pérez-Arévalo, R., Jiménez-Caldera, J., Serrano-Montes, J. L., Rodrigo- Comino, J., Therán-Nieto, K., & Caballero-Calvo, A. (2024). Enhancing urban resilience: strategic management and action plans for cyclonic events through socially constructed risk processes. Urban Science, 8(2), 43. https://doi. org/10.3390/urbansci8020043
  • Pieroni, A., Scarpato, N., Di Nunzio, L., Fallucchi, F., & Raso, M. (2018). Smarter city: Smart energy grid based on blockchain technology. International Journal on Advanced Science, Engineering and Information Technology, 8(1), 298-306. https://doi.org/10.18517/ijaseit.8.1.4954
  • Pirrone, N., Mazzetti, P., Cinnirella, S., Athanasopoulou, E., Gerasopoulos, E., Klánová, J., Lehmann, A., Pau, J. M., Petäjä, T., Pokorný, L., & Šebková, K. (2022). The science-policy interfaces of the european network for observing our changing planet: from earth observation data to policy-oriented decisions. Environmental Science & Policy, 137, 359–372. https://doi.org/10.1016/j. envsci.2022.09.006
  • Rana, I. A., Asim, M., Aslam, A. B., & Jamshed, A. (2021). Disaster management cycle and its application for flood risk reduction in urban areas of Pakistan. Urban Climate, 38, 100893. https://doi.org/10.1016/j. uclim.2021.100893
  • Reinisch, C., Kofler, M., Iglesias, F., & Kastner, W. (2011). Thinkhome energy efficiency in future smart homes. EURASIP Journal on Embedded Systems, 2011(1), 104617. https://doi.org/10.1155/2011/104617
  • Ritchie, H., Rosado, P., & Roser, M. (2023). CO₂ and greenhouse gas emissions. Our World In Data. https://ourworldindata.org/co2-and-greenhousegas- emissions
  • Rocha, P., Siddiqui, A., & Stadler, M. (2015). Improving energy efficiency via smart building energy management systems: A comparison with policy measures. Energy and Buildings, 88, 203–213. https://doi.org/10.1016/j. enbuild.2014.11.07
  • Saja, A. M. A., Teo, M., Goonetilleke, A., & Ziyath, A. M. (2021). A critical review of social resilience properties and pathways in disaster management. International Journal of Disaster Risk Science, 12(6), 790–804. https://doi. org/10.1007/s13753-021-00378-y
  • Santamouris, M., & Vasilakopoulou, K. (2021). Present and future energy consumption of buildings: Challenges and opportunities towards decarbonisation. E-Prime - Advances in Electrical Engineering, Electronics and Energy, 1, 100002. https://doi.org/10.1016/J.Prime.2021.100002
  • Savur, D. (2024). Integrating blockchain in smart building systems: A framework for efficiency and scalability (Thesis No. 909055) [Master's thesis, Ankara Yıldırım Beyazıt University]. Council of Higher Education Thesis Center. https://tez.yok.gov.tr/
  • Sepasgozar, S., Karimi, R., Farahzadi, L., Moezzi, F., Shirowzhan, S., M. Ebrahimzadeh, S., Hui, F., & Aye, L. (2020). A systematic content review of artificial intelligence and the internet of things applications in smart home. Applied Sciences, 10(9), 3074. https://doi.org/10.3390/app10093074
  • Sethi, B. K., Mukherjee, D., Singh, D., Misra, R. K., & Mohanty, S. R. (2020). Smart Home energy management system under false data injection attack. International Transactions on Electrical Energy Systems, 30(7) , e12411. https://doi.org/10.1002/2050-7038.12411
  • Shao, W., Su, X., Lu, J., Liu, J., Yang, Z., Mei, C., Liu, C., & Lu, J. (2021). Urban resilience of Shenzhen City under climate change. Atmosphere, 12(5), 537. https://doi.org/10.3390/atmos12050537
  • Shapi, M. K. M., Ramli, N. A., & Awalin, L. J. (2021). Energy consumption prediction by using machine learning for smart building: Case study in Malaysia. Developments in the Built Environment, 5, 100037. https://doi.org/10.1016/j. dibe.2020.100037
  • Sharma, K., Anand, D., Sabharwal, M., Tiwari, P. K., Cheikhrouhou, O., & Frikha, T. (2021). A disaster management framework using internet of thingsbased interconnected devices. Mathematical Problems in Engineering, 2021, 1–21. https://doi.org/10.1155/2021/9916440
  • Shen, P., Wei, S., Shi, H., Gao, L., & Zhou, W. H. (2023). Coastal flood risk and smart resilience evaluation under a changing climate. Ocean-Land- Atmosphere Research, 2, 0029. https://doi.org/10.34133/olar.0029
  • Sloane, A. (Ed.). (2005). Home-Oriented Informatics and Telematics: Proceedings of the IFIP WG 9.3 HOIT2005 Conference (Vol. 178). Springer Science & Business Media.
  • Spiridonov, V., & Ćurić, M. (2021). Climate and climate change. In V. Spiridonov & M. Ćurić (Eds.), Fundamentals of Meteorology (pp. 377–397). Springer International Publishing. https://doi.org/10.1007/978-3-030-52655- 9_24
  • Swain, D. L., Singh, D., Touma, D., & Diffenbaugh, N. S. (2020). Attributing extreme events to climate change: A new frontier in a warming World. One Earth, 2(6), 522–527. https://doi.org/10.1016/j.oneear.2020.05.011
  • Tao, H., Yaseen, Z. M., Tan, M. L., Goliatt, L., Heddam, S., Halder, B., Sa'adi, Z., Ahmadianfar, I., Homod, R. Z., & Shahid, S. (2024). High-resolution remote sensing data-based urban heat island study in chongqing and Changde City, China. Theoretical And Applied Climatology, 155(7), 7049–7076. https:// doi.org/10.1007/s00704-024-05041-2
  • Tonmoy, F. N., Hasan, S., & Tomlinson, R. (2020). Increasing coastal disaster resilience using smart city frameworks: Current state, challenges, and opportunities. Frontiers In Water, 2, 3. https://doi.org/10.3389/frwa.2020.00003
  • Top, A. M., Ayçam, İ., & Soyluk, A. (2025). Urban heat island effect in the context of architecture and disaster management: A systematic bibliometric review. Building Services Engineering Research & Technology, 47(1), 119-143. https://doi.org/10.1177/01436244251386728
  • Turgut, Z., Aydın, G. Z. G., & Sertbas, A. (2016). Indoor localization techniques for smart building environment. Procedia Computer Science, 83, 1176–1181. https://doi.org/10.1016/j.procs.2016.04.242
  • Türkyılmaz, S., & Altındag, E. (2022). Analysis of smart home systems in the context of the internet of things in terms of consumer experience. International Review of Management and Marketing, 12(1), 19–31. https://doi. org/10.32479/irmm.12709
  • United Nations. (1992). United Nations Framework Convention on Climate Change. https://unfccc.int/resource/docs/convkp/conveng.pdf
  • Van Eck, N. J., & Waltman, L. (2024). VOSviewer (Version 1.6.20) [Computer software]. Retrieved December, 2, 2025 from https://www. vosviewer.com
  • Verma, A., Prakash, S., Srivastava, V., Kumar, A., & Mukhopadhyay, S. C. (2019). Sensing, controlling, and Iot infrastructure in smart building: A review. IEEE Sensors Journal, 19(20), 9036–9046. https://doi.org/10.1109/ JSEN.2019.2922409
  • White, R.M., 1979: The World Climate Conference (WCC): Report by the Conference Chairman. WMO Bulletin, 28, 3, 177-178.
  • World Health Organization. (2002). Environmental health in emergencies and disasters: A practical guide. https://www.who.int/publications/i/ item/9241545410
  • Wiik, M. K., Fufa, S. M., Fjellheim, K., Lien, S. K., Krogstie, J., Ahlers, D., ... & Gustavsen, A. (2022). Zero Emission Neighbourhoods in Smart Cities. Definition, Key Performance Indicators and Assessment Criteria: Version, 3.
  • Xie, X., Ramakrishna, S., & Manganelli, M. (2022). Smart building technologies in response to COVID-19. Energies, 15(15), 5488. https://doi. org/10.3390/en15155488
  • Xu, Z., Guan, X., Jia, Q. S., Wu, J., Wang, D., & Chen, S. (2012). Performance analysis and comparison on energy storage devices for smart building energy management. IEEE Transactions on Smart Grid, 3(4), 2136– 2147. https://doi.org/10.1109/tsg.2012.2218836
  • Yar, H., Khan, Z. A., Ullah, F. U. M., Ullah, W., & Baik, S. W. (2023). A modified yolov5 architecture for efficient fire detection in smart cities. Expert Systems with Applications, 231, 120465. https://doi.org/10.1016/j. eswa.2023.120465
  • Yu, L., Qin, S., Zhang, M., Shen, C., Jiang, T., & Guan, X. (2021). A review of deep reinforcement learning for smart building energy management. IEEE Internet of Things Journal, 8(15), 12046–12063. https://doi.org/10.1109/ jiot.2021.3078462
  • Zhang, D., Shah, N., & Papageorgiou, L. G. (2013). Efficient energy consumption and operation management in a smart building with microgrid. Energy Conversion and Management, 74, 209–222. https://doi.org/10.1016/j. enconman.2013.04.038
  • Zhang, Y., Li, X., & Liu, Q. (2025). Advancing urban resilience: a multi-hazard risk perspective on frontier evolution, research hotspots, and practical exploration. Urban Climate, 60, 102342. https://doi.org/10.1016/j. uclim.2025.102342
  • Zhu, D., Li, X., & Li, H. (2025). Research on the infrastructure resilience system and sustainable development of coastal cities in the Bohai Sea, China: A multi-model and spatiotemporal heterogeneity analysis based on CAS. Sustainability, 17(18), 8232. https://doi.org/10.3390/su17188232
  • Zhu, S., Li, D., Chen, M., & Zhang, Y. (2024). Climate change scenario simulations for urban flood resilience with system dynamics approach: A case study of smart city Shanghai in Yangtze River Delta Region. International Journal of Disaster Risk Reduction, 112, 104801. https://doi.org/10.1016/j. ijdrr.202 4.104801