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Applications, Modern Trends, and Challenges of Multiscale Modeling in Smart Cities
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Author(s): Dipannita Mondal (Dr. D.Y. Patil College of Engineering and Innovation, India), Archana Ratnaparkhi (Vishwakarma Institute of Information Technology, India), Abhijeet Deshpande (Vishwakarma Institute of Information Technology, India), Vivek Deshpande (Vishwakarma Institute of Information Technology, India), Aniruddha Prakash Kshirsagar (Karmaveer Bhaurao Patil College of Engineering, India)and Sabyasachi Pramanik (Haldia Institute of Technology, India)
Copyright: 2023
Pages: 23
Source title:
Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities
Source Author(s)/Editor(s): Sabyasachi Pramanik (Haldia Institute of Technology, India)and K. Martin Sagayam (Karunya Institute of Technology and Sciences, India)
DOI: 10.4018/978-1-6684-6408-3.ch001
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Abstract
Megacities are intricate systems that struggle with difficulties including overcrowding, subpar urban design and planning, inadequate mobility and public transportation, subpar governance, problems with climate change, subpar water and sewage infrastructure, problems with waste and health, and unemployment. By maximising the use of available resources and space for the benefit of residents, smart cities have evolved as a solution to these problems. A smart city model sees the city as a complex adaptive system made up of residents, services, and resources that learn from one another and change across time and space. City planners must adopt a new methodical and modelling approach in order to address the fundamental concerns of dynamic growth and complexity. A method that may be utilised to comprehend complicated adaptive systems better is multiscale modelling (MM). To increase system efficiency and reduce computing complexity and cost, the MM strives to address complicated issues at several sizes, including micro, meso, and macro.
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