Machine Learning for Smart Cities: A Survey

C. Mahamuni, Zuber Sayyed, Ayush Mishra
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引用次数: 1

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.
智能城市的机器学习:一项调查
智慧城市利用信息通信技术(ICT)工具来提高运营效率并提供优质服务。它的目的是使核心基础设施可用,提高生活质量。人工智能(AI)方法用于改善智慧城市的关键特征,以提高生活质量。智慧城市的可持续发展需要确保快速城市化不影响自然环境。机器学习(ML)是人工智能的一个重要子集,可以为新兴智能城市的可持续发展做出贡献。文献表明,研究界可以使用机器学习(ML)和深度学习(DL)来改善智慧城市的各种属性。这些包括预测空气质量、作物管理、预测天气状况,如降雨、湿度、雾、交通、供水、基础设施等。本文对智慧城市概念、智慧城市的可持续性、智慧城市的功能方面进行了文献研究,并对机器学习和深度学习在智慧城市中的应用进行了调查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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