Enhancing disaster management in smart cities through MCDM-AHP analysis amid 21st century challenges
Abstract
In the era of rapid urbanization and technological progress, smart cities offer a promising solution to multifaceted global challenges, leveraging advanced technologies to optimize resources and enhance the quality of life; however, this interconnectedness also exposes them to novel vulnerabilities, particularly in the face of natural and man-made disasters, necessitating inventive strategies to ensure resilience against cyber threats and extreme weather events. This article delves into the exploration of smart cities’ diverse aspects and the categories of disasters they face, followed by an analysis of strategic mitigation approaches and their underlying criteria; it subsequently introduces the Multi-Criteria Decision-Making methodology, particularly Analytical Hierarchy Process (AHP), as a robust tool for systematic evaluation and prioritization of disaster management strategies in the increasingly complex landscape. The study’s analysis of relative weights underscores the pivotal role of Resilience Enhancement and Communication Redundancy as primary considerations in evaluating disaster management strategies for smart cities, while other criteria such as Accuracy and Timeliness, Scalability and Adaptability, Cost-effectiveness, Ethical and Privacy Considerations, and Training and Skill Requirements assume varying degrees of importance in supporting roles, providing valuable insights into the decision-making process. The assessment of alternative strategies highlights their prioritization in effective disaster management for smart cities, with notable emphasis on Citizen Engagement and Education, Early Warning Systems, and data analytics; further strategies such as Integrated Communication Systems, Resilient Infrastructure Design, Drones and Robotics, Artificial Intelligence Algorithms, and IoT-enabled Sensors and Monitoring exhibit varying degrees of significance, offering insights into their roles and potential contributions to disaster management strategies based on their weighted sums. This research has practical significance, guiding stakeholders like urban planners, policymakers, and disaster management professionals to enhance smart city resilience and prioritize strategies based on critical factors, ultimately enabling effective disaster management in smart cities amid 21st-century challenges.References
[1] Alam T. IBchain: Internet of Things and Blockchain Integration Approach for Secure Communication in Smart Cities. Informatica. 2021, 45(3). doi: 10.31449/inf.v45i3.3573
[2] Ales F. Evolution of Smart Cities Movements Toward Resilient Cities. A Comparative Analysis of Case Studies in Tokyo, Japan. 2019.
[3] Ali M, Naeem F, Adam NH, et al. Integration of Data Driven Technologies in Smart Grids for Resilient and Sustainable Smart Cities: A Comprehensive Review. ArXiv 2023.
[4] Alkhammash EH, Jussila J, Lytras MD, et al. Annotation of Smart Cities Twitter Micro-Contents for Enhanced Citizen’s Engagement. IEEE Access. 2019, 7: 116267-116276. doi: 10.1109/access.2019.2935186
[5] Alsamhi SH, Ma O, Ansari MS, et al. Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities. IEEE Access. 2019, 7: 128125-128152. doi: 10.1109/access.2019.2934998
[6] Andersen KN, Kim BJ. Smart Cities at a Cross Road: How South Korea is Balancing Safety, Creativity, Innovation, Economic Growth, and Sustainability. The 21st Annual International Conference on Digital Government Research. 2020.
[7] Bellini P, Nesi P, Pantaleo G. IoT-Enabled Smart Cities: A Review of Concepts, Frameworks and Key Technologies. Applied Sciences. 2022, 12(3): 1607. doi: 10.3390/app12031607
[8] Bouramdane AA. Agrivoltaics, what exactly are we talking about (French)? Énergie/mines & Carrières 2022. doi: 10. 5281/zenodo.7594342
[9] Bouramdane AA. Assessment of CMIP6 Multi-Model Projections Worldwide: Which Regions Are Getting Warmer and Are Going through a Drought in Africa and Morocco? What Changes from CMIP5 to CMIP6? Sustainability. 2022, 15(1): 690. doi: 10.3390/su15010690
[10] Bouramdane AA. Climate Resilience: Insights from Global Negotiations and Morocco’s Path to Sustainability. Lambert Academic Publishing (LAP). 2023.
[11] Bouramdane AA. Climate Risks and Energy Transition in Morocco: Vulnerability to Climate Losses and Damages and Uncertainty in the Renewable Electricity Mix Under Different Penetration. Lambert Academic Publishing (LAP); 2023.
[12] Bouramdane AA. Cyberattacks in Smart Grids: Challenges and Solving the Multi-Criteria Decision-Making for Cybersecurity Options, Including Ones That Incorporate Artificial Intelligence, Using an Analytical Hierarchy Process. Journal of Cybersecurity and Privacy. 2023, 3(4): 662-705. doi: 10.3390/jcp3040031
[13] Bouramdane AA. Determining Vulnerable Areas to Warming and Drought in Africa and Morocco Based on CMIP6 Projections: Towards the Implementation of Mitigation and Adaptation Measures. 2023. doi: 10.5194/egusphere-egu23-2456
[14] Bouramdane AA. Drought: Will the extreme gradually become the norm (French)? Energy/mining & Careers 2022. doi:10.5281/zenodo.7594311
[15] Bouramdane AA. How to manage vulnerabilities in the renewable energy environment? Leadvent Group, Renewable Energy Cyber Security Forum, Berlin, Germany 2023; doi: 10.5281/zenodo.7730062
[16] Bouramdane AA. Identifying Large-Scale Photovoltaic and Concentrated Solar Power Hot Spots: Multi-Criteria Decision-Making Framework. World Academy of Science, Engineering and Technology International Journal of Energy and Power Engineering 2023; 17(2). doi: 10.5281/zenodo.7324107
[17] Bouramdane AA. Moroccan electricity mix: Challenges facing the climate emergency (French). Energie/mines & Carrières 2021. doi:10.5281/zenodo.7594427
[18] Bouramdane AA. Morocco’s road to a climate-resilient energy transition: Emissions drivers, solutions, and barriers. 2023. doi:10.13140/RG.2.2.30108.77442/1
[19] Bouramdane AA. Places Most Sensitive to Climate Change Requiring Mitigation and Adaptation Measures (French). Energie/mines & Carrières 2023. doi: 10.5281/zenodo.7937556
[20] Bouramdane AA. Potential Site for Offshore Floating Photovoltaic Systems in Morocco: Evaluation Criteria Required Considering Climate Change Effects to Achieve the Energy Trilemma. Lambert Academic Publishing (LAP); 2023.
[21] Bouramdane AA. Preservation of water resources and energy transition: Floating photovoltaics update (French). Energy/mining & Careers 2023. doi:10.5281/zenodo.8021774
[22] Bouramdane AA. PV, CSP and wind power in Morocco: Variable geometry integration (French). Énergie/mines & Carrières 2022. doi: 10.5281/zenodo.7594221
[23] Bouramdane AA. Scenarios of Large-Scale Solar Integration with Wind in Morocco: Impact of Storage, Cost, Spatio-Temporal Complementarity and Climate Change [Thesis]. Institut Polytechnique de Paris; 2021.
[24] Bouramdane AA. Scorching heat, repeated gigantic fires: Signs of climate change (French)? Energie/mines & Carrières 2022. doi: 10.5281/zenodo.7594264
[25] Bouramdane AA. Site suitability of offshore wind energy: A combination of geographic referenced information and analytic hierarchy process. World Academy of Science, Engineering and Technology International Journal of Energy and Power Engineering 2023; 17(2). doi: 10.5281/zenodo.7324191
[26] Bouramdane AA. Solutions to reduce pressure on water (French). Energy/mining & Careers 2023. doi:10. 5281/zenodo.8021765
[27] Bouramdane AA. Spatial suitability assessment of onshore wind systems using the analytic hierarchy process. World Academy of Science, Engineering and Technology International Journal of Energy and Power Engineering 2023; 17(7). doi: 10.5281/zenodo.7324223
[28] Bouramdane AA. What is the relationship between agriculture and climate change (French)? Énergie/mines & Carrières 2023. doi: 10.5281/zenodo.7730008
[29] Bouramdane AA. Why mitigation and adaptation to climate change are complementary (French)? Energie/mines & Carrières 2022. doi: 10.5281/zenodo.7594404
[30] Britannica. Morocco Earthquake of 2023. Available online: https://www.britannica.com/event/ Morocco-earthquake-of-2023 (accessed on 29 November 2023).
[31] Cesario E. Big data analytics and smart cities: applications, challenges, and opportunities. Frontiers in Big Data. 2023, 6. doi: 10.3389/fdata.2023.1149402
[32] Cheng B, Longo S, Cirillo F, et al. Building a Big Data Platform for Smart Cities: Experience and Lessons from Santander. 2015 IEEE International Congress on Big Data. Published online June 2015. doi: 10.1109/bigdatacongress.2015.91
[33] Chourasia K. Role of Smart Traffic Management & Intelligent Street Lighting in Smart Cities. International Journal of Research, 2019. 6: 464–466.
[34] Dalal S, Bassu D. Deep analytics for workplace risk and disaster management. IBM Journal of Research and Development. 2020, 64(1/2): 14: 1-14: 9. doi: 10.1147/jrd.2019.2945693
[35] Danishuddin, Kumar V, Faheem M, et al. A decade of machine learning-based predictive models for human pharmacokinetics: Advances and challenges. Drug Discovery Today. 2022, 27(2): 529-537. doi: 10.1016/j.drudis.2021.09.013
[36] Dash B, Sharma P. Role of Artificial Intelligence in Smart Cities for Information Gathering and Dissemination (A Review). Academic Journal of Research and Scientific Publishing. 2022, 4(39): 58-75. doi: 10.52132/ajrsp.e.2022.39.4
[37] di Vimercati SDC, Foresti S, Livraga G, et al. Digital Infrastructure Policies for Data Security and Privacy in Smart Cities. Smart Cities Policies and Financing 2022. Available online: https://api.semanticscholar.org/CorpusID:246166961 (accessed on 29 November 2023).
[38] Eskhita R. Dubai and Barcelona as Smart Cities: Some Reflections on Data Protection Law and Privacy. SSRN Electronic Journal. 2021. doi: 10.2139/ssrn.3944895
[39] Fan C. Integrating Human Mobility and Infrastructure Design in Digital Twin to Improve Equity and Resilience of Cities. 2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI). Published online October 24, 2022. doi: 10.1109/dtpi55838.2022.9998905
[40] Gade DS. Reinventing Smart Water Management System through ICT and IoT Driven Solution for Smart Cities. International Journal of Applied Engineering and Management Letters. 2021: 132-151. doi: 10.47992/ijaeml.2581.7000.0109
[41] Gorgol NK. The Analysis of the Relationship Between the Idea of Smart City and the Urban Form on the Example of Oslo and Vienna. Available online: https://www.ejournals.eu/housingenvironment/2018/(23)2018/art/12635/ (accessed on 29 November 2023).
[42] Haggart B, Spicer Z. Infrastructure, smart cities and the knowledge economy: Lessons for policymakers from the Toronto Quayside project. Canadian Public Administration. 2022, 65(2): 295-313. doi: 10.1111/capa.12460
[43] Hartley K. Public Perceptions About Smart Cities: Governance and Quality-of-Life in Hong Kong. Social Indicators Research. 2023, 166(3): 731-753. doi: 10.1007/s11205-023-03087-9
[44] Herath HMKKMB, Mittal M. Adoption of artificial intelligence in smart cities: A comprehensive review. International Journal of Information Management Data Insights. 2022, 2(1): 100076. doi: 10.1016/j.jjimei.2022.100076
[45] Husna C, Firdaus R, Wardani E, et al. Disaster preparedness among disaster management agency officers: a study from rural and urban areas in Aceh, Indonesia. International Journal of Disaster Resilience in the Built Environment. 2021, 13(4): 484-497. doi: 10.1108/ijdrbe-02-2021-0015
[46] Jabłon´ska A. Smart Cities in Practice. A Comparative Case Study Between Warsaw, Gdynia, Copenhagen and Malmö. A Public Actor’s Perspective with a Secondary Focus on Collaboration and Digitization. 2018.
[47] Jokanović V. Smart Healthcare in Smart Cities. Towards Smart World. Published online December 13, 2020: 45-72. doi: 10.1201/9781003056751-4
[48] Joo YM. Developmentalist smart cities? the cases of Singapore and Seoul. International Journal of Urban Sciences. 2021, 27(sup1): 164-182. doi: 10.1080/12265934.2021.1925143
[49] Khan H, Kushwah KK, Maurya MR, et al. Machine learning driven intelligent and self adaptive system for traffic management in smart cities. Computing. 2022, 104(5): 1203-1217. doi: 10.1007/s00607-021-01038-1
[50] Khatri KC J, Fitzgerald G, Poudyal Chhetri MB. Health Risks and Challenges in Earthquake Responders in Nepal: A Qualitative Research. Prehospital and Disaster Medicine. 2019, 34(03): 274-281. doi: 10.1017/s1049023x19004370
[51] Kolomvatsos K, Anagnostopoulos C. Reinforcement Learning for Predictive Analytics in Smart Cities. Informatics. 2017, 4(3): 16. doi: 10.3390/informatics4030016
[52] Kuecker GD, Hartley K. How Smart Cities Became the Urban Norm: Power and Knowledge in New Songdo City. Annals of the American Association of Geographers. 2019, 110(2): 516-524. doi: 10.1080/24694452.2019.1617102
[53] Kuzior A, Pakhnenko O, Tiutiunyk I, et al. E-Governance in Smart Cities: Global Trends and Key Enablers. Smart Cities. 2023, 6(4): 1663-1689. doi: 10.3390/smartcities6040078
[54] Laitinen I, Piazza R, Stenvall J. Adaptive learning in smart cities – The cases of Catania and Helsinki. Journal of Adult and Continuing Education. 2017, 23(1): 119-137. doi: 10.1177/1477971417691781
[55] Li Z, Al Hassan R, Shahidehpour M, et al. A Hierarchical Framework for Intelligent Traffic Management in Smart Cities. IEEE Transactions on Smart Grid. 2019, 10(1): 691-701. doi: 10.1109/tsg.2017.2750542
[56] Lin YC, Cheung WF. Developing WSN/BIM-Based Environmental Monitoring Management System for Parking Garages in Smart Cities. Journal of Management in Engineering. 2020, 36(3). doi: 10.1061/(asce)me.1943-5479.0000760
[57] Liu Y, Yang C, Jiang L, et al. Intelligent Edge Computing for IoT-Based Energy Management in Smart Cities. IEEE Network. 2019, 33(2): 111-117. doi: 10.1109/mnet.2019.1800254
[58] Maltezos E, Karagiannidis L, Dadoukis A, et al. Public Safety in Smart Cities under the Edge Computing Concept. 2021 IEEE International Mediterranean Conference on Communications and Networking (MeditCom). 2021. 88-93.
[59] Mashhadi A, Winder SG, Lia EH, et al. Quantifying Biases in Social Media Analysis of Recreation in Urban Parks. 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). 2020. doi: 10.1109/percomworkshops48775.2020.9156262
[60] Noori N, Hoppe T, de Jong M. Classifying Pathways for Smart City Development: Comparing Design, Governance and Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi. Sustainability. 2020, 12(10): 4030. doi: 10.3390/su12104030
[61] Nusrat F, Haque M, Rollend D, et al. A High-Resolution Earth Observations and Machine Learning-Based Approach to Forecast Waterborne Disease Risk in Post-Disaster Settings. Climate. 2022, 10(4): 48. doi: 10.3390/cli10040048
[62] Oh N. Collective decision-making for developing emergency management capabilities. International Journal of Emergency Services. 2020, 9(2): 179-202. doi: 10.1108/ijes-06-2019-0025
[63] Parkhe GG. Smart water management system in tier II cities in India in achieving the SDGs. International journal of health sciences. 7, 2022: 5127-5135. doi: 10.53730/ijhs.v6ns3.7019
[64] Poongodi M, Sharma A, Hamdi M, et al. Smart healthcare in smart cities: wireless patient monitoring system using IoT. The Journal of Supercomputing. 2021, 77(11): 12230-12255. doi: 10.1007/s11227-021-03765-w
[65] Rana IA, Asim M, Aslam AB, et al. Disaster management cycle and its application for flood risk reduction in urban areas of Pakistan. Urban Climate. 2021, 38: 100893. doi: 10.1016/j.uclim.2021.100893
[66] Renaud J, Karam R, Salomon M, et al. Deep learning and gradient boosting for urban environmental noise monitoring in smart cities. Expert Systems with Applications. 2023, 218: 119568. doi: 10.1016/j.eswa.2023.119568
[67] Riaz K, McAfee M, Gharbia SS. Management of Climate Resilience: Exploring the Potential of Digital Twin Technology, 3D City Modelling, and Early Warning Systems. Sensors. 2023, 23(5): 2659. doi: 10.3390/s23052659
[68] Saaty RW. The analytic hierarchy process—what it is and how it is used. Mathematical Modelling. 1987, 9(3-5): 161-176. doi: 10.1016/0270-0255(87)90473-8
[69] Saaty TL. A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology. 1977, 15(3): 234-281. doi: 10.1016/0022-2496(77)90033-5
[70] Saaty TL. Decision Making for Leaders: The Analytical Hierarchy Process for Decisions in a Complex World. 1982.
[71] Saaty TL. Decision making with the analytic hierarchy process. International Journal of Services Sciences. 2008, 1(1): 83. doi: 10.1504/ijssci.2008.017590
[72] Saaty TL. Fundamentals of Decision Making and Priority Theory with the Analytic Hierarchy Process. 2000.
[73] Saaty TL. How to Make a Decision: The Analytic Hierarchy Process. Interfaces. 1994, 24(6): 19-43. doi: 10.1287/inte.24.6.19
[74] Saaty TL. The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. 1990.
[75] Saaty TL. What is the Analytic Hierarchy Process. 1988.
[76] Sambargi S, Tripathi M. Waste Management in Smart Cities. International Scientific Journal of Engineering and Management 2023. 2(4). doi: 10.55041/isjem00402
[77] Sontiwanich P, Boonchai C, Beeton RJS. An Unsustainable Smart City: Lessons from Uneven Citizen Education and Engagement in Thailand. Sustainability. 2022, 14(20): 13315. doi: 10.3390/su142013315
[78] Sosunova I, Porras J. IoT-Enabled Smart Waste Management Systems for Smart Cities: A Systematic Review. IEEE Access. 2022, 10: 73326-73363. doi: 10.1109/access.2022.3188308
[79] Srinivasan R, Mohan A, Srinivasan P. Privacy conscious architecture for improving emergency response in smart cities. 2016 Smart City Security and Privacy Workshop (SCSP-W). 2016. doi: 10.1109/scspw.2016.7509559
[80] Tham JCK, Verhulsdonck G. Smart Education in Smart Cities: Layered Implications for Networked and Ubiquitous Learning. IEEE Transactions on Technology and Society. 2023, 4(1): 87-95. doi: 10.1109/tts.2023.3239586
[81] UlAmin R, Akram M, Ullah N, et al. IoT Enabled Air Quality Monitoring for Health-Aware Commuting Recommendation in Smart Cities. International Journal of Advanced Computer Science and Applications. 2020, 11(6). doi: 10.14569/ijacsa.2020.0110637
[82] Unlocking Investment for Digital Infrastructure and Smart Cities. The State of the Digital Economy in the Commonwealth. 2020.
[83] Vishnu S, Ramson SRJ, Senith S, et al. IoT-Enabled Solid Waste Management in Smart Cities. Smart Cities. 2021, 4(3): 1004-1017. doi: 10.3390/smartcities4030053
[84] Yigitcanlar T, Butler L, Windle E, et al. Can Building “Artificially Intelligent Cities” Safeguard Humanity from Natural Disasters, Pandemics, and Other Catastrophes? An Urban Scholar’s Perspective. Sensors. 2020, 20(10): 2988. doi: 10.3390/s20102988
[85] Yigitcanlar T, Han H, Kamruzzaman Md, et al. The making of smart cities: Are Songdo, Masdar, Amsterdam, San Francisco and Brisbane the best we could build? Land Use Policy. 2019, 88: 104187. doi: 10.1016/j.landusepol.2019.104187
[86] Yukio H. Identifying Land Use Changes and the Related Problems in Northern States of India. Japan Geoscience Union 2015.
[87] Zhang X. Analysis of Smart Cities in Singapore Based Artificial Intelligence. 2021 IEEE International Conference on Robotics, Automation and Artificial Intelligence (RAAI); 21 April 2021. doi: 10.1109/raai52226.2021.9507784
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