| Title |
Machine Learning for Smart Cities: A Survey |
| ID_Doc |
40308 |
| Authors |
Mahamuni, CV; Sayyed, Z; Mishra, A |
| Title |
Machine Learning for Smart Cities: A Survey |
| Year |
2022 |
| Published |
|
| DOI |
10.1109/IPRECON55716.2022.10059521 |
| Abstract |
Smart Cities utilize Information and Communication Technology (ICT) tools to improve operational efficiency and provide excellent service. It aims to make the core infrastructure available and enhance the quality of life. Artificial Intelligence (AI) approaches are used to improve the critical features of a smart city to enhance the quality of life. Smart cities' sustainable development is needed to ensure that rapid urbanization does not affect the natural environment. Machine Learning (ML) is an essential subset of Artificial Intelligence that can contribute to the expansion of emerging smart cities with sustainability. The literature shows that the research community can use Machine Learning (ML) and Deep Learning (DL) to improve the various smart city attributes. These include prediction of air quality, crop management, forecasting weather conditions like rainfall, humidity, fog, transportation, water supply, infrastructure, etc. This paper presents a literature-based study of the smart city concept, sustainability in smart cities, the functional aspects of smart cities, and a survey related to the use of Machine Learning and Deep Learning in it. |
| Author Keywords |
Smart City; Machine Learning; Air quality; Smart Health; Smart Education; Smart Energy; Smart Transportation/Mobility |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:001022949500050 |
| WoS Category |
Green & Sustainable Science & Technology; Energy & Fuels |
| Research Area |
Science & Technology - Other Topics; Energy & Fuels |
| PDF |
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