Khan, A.; Aslam, S.; Aurangzeb, K.; Alhussein, M.; Javaid, N. Multiscale Modeling in Smart Cities: A Survey on Applications, Current Trends, and Challenges. Sustainable Cities and Society 2022, 78, 103517, doi:10.1016/j.scs.2021.103517.
Khan, A.; Aslam, S.; Aurangzeb, K.; Alhussein, M.; Javaid, N. Multiscale Modeling in Smart Cities: A Survey on Applications, Current Trends, and Challenges. Sustainable Cities and Society 2022, 78, 103517, doi:10.1016/j.scs.2021.103517.
Khan, A.; Aslam, S.; Aurangzeb, K.; Alhussein, M.; Javaid, N. Multiscale Modeling in Smart Cities: A Survey on Applications, Current Trends, and Challenges. Sustainable Cities and Society 2022, 78, 103517, doi:10.1016/j.scs.2021.103517.
Khan, A.; Aslam, S.; Aurangzeb, K.; Alhussein, M.; Javaid, N. Multiscale Modeling in Smart Cities: A Survey on Applications, Current Trends, and Challenges. Sustainable Cities and Society 2022, 78, 103517, doi:10.1016/j.scs.2021.103517.
Abstract
Megacities are complex systems facing the challenges of overpopulation, poor urban design and planning, poor mobility and public transport, poor governance, climate change issues, poor sewerage and water infrastructure, waste and health issues, and unemployment. Smart cities have emerged to address these challenges by making the best use of space and resources for the benefit of citizens. A smart city model views the city as a complex adaptive system consisting of services, resources, and citizens that learn through interaction and change in both the spatial and temporal domains. The characteristics of dynamic development and complexity are key issues for city planners that require a new systematic and modeling approach. Multiscale modeling (MM) is an approach that can be used to better understand complex adaptive systems. The MM aims to solve complex problems at different scales, i.e., micro, meso, and macro, to improve system efficiency and mitigate computational complexity and cost. In this paper, we present an overview of MM in smart cities. First, this study discusses megacities, their current challenges, and their emergence to smart cities. Then, we discuss the need of MM in smart cities and its emerging applications. Finally, the study highlights current challenges and future directions related to MM in smart cities, which provide a roadmap for the optimized operation of smart city systems.
Computer Science and Mathematics, Computer Science
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