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Smart city article details
| Title | Smart Urban Metabolism: A Big-Data And Machine Learning Perspective |
|---|---|
| ID_Doc | 51657 |
| Authors | Ghosh R.; Sengupta D. |
| Year | 2023 |
| Published | Urban Metabolism and Climate Change: Perspective for Sustainable Cities |
| DOI | http://dx.doi.org/10.1007/978-3-031-29422-8_16 |
| Abstract | Smart urban metabolism is a contemporary conception of urban metabolism which includes modern-day technologies dealing with the complex challenges of growing smart cities. Traditionally, urban metabolism deals with the influx-efflux of energy and flow of materials through urban space. However, with the growing needs of smart cities, these flow patterns are transiting as a complex network and are subject to interdisciplinary understanding. Furthermore, data availability is a major challenge faced by city planners due to the lack of data inventories and appro-priate data management solutions to handle massive datasets, arising from these complex flow patterns. This is ensuing to inefficient adaptation of urban metabolism approaches, especially in developing economies. Thus, the situation remains grave when it comes to resource management of a smart city, and how urban areas may additionally deal with intricate issues like climate change when they are striving to understand their own material and energy cycling. In this chapter, we therefore, discuss how technologies like machine learning can equip urban metabolism, for its transition to “Smart Urban Metabolism.” The chapter presents use of technolo-gies like big-data and machine learning, as effective methodologies to channelize and manage heterogeneous multidimensional datasets, adoption of practices, devel-oping self-learning machine learning models, and gain novel insights via predictive analytics, in “Smart Urban Metabolism.” Precisely, for urban planners, the “Smart Urban Metabolism” can potentially be an effective approach for identifying complex issues in the flow patterns of energy and material in an urban space. This approach is a step toward sustainable city development. © The Author(s). |
| Author Keywords | Big-data analytics; Machine learning; Smart cities; Smart urban metabolism; Sustainable development; Urban metabolism |
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