Abstract
Smart cities (SC) promote economic development, improve the welfare of their citizens, and help in the ability of people to use technologies to build sustainable services. However, computational methods are necessary to assist in the process of creating smart cities because they are fundamental to the decision-making process, assist in policy making, and offer improved services to citizens. As such, the aim of this research is to present a systematic review regarding data mining (DM) and machine learning (ML) approaches adopted in the promotion of smart cities. The Methodi Ordinatio was used to find relevant articles and the VOSviewer software was performed for a network analysis. Thirty-nine significant articles were identified for analysis from the Web of Science and Scopus databases, in which we analyzed the DM and ML techniques used, as well as the areas that are most engaged in promoting smart cities. Predictive analytics was the most common technique and the studies focused primarily on the areas of smart mobility and smart environment. This study seeks to encourage approaches that can be used by governmental agencies and companies to develop smart cities, being essential to assist in the Sustainable Development Goals.
Highlights
According to a United Nations [1] report, it is estimated that 68% of all people will live in urban areas by 2050
To identify the existing knowledge related to the use of data mining (DM) and machine learning (ML) in the promotion of smart cities (SC), a systematic review was conducted
In order to obtain answers to the two research questions, we used a systematic review and present the articles gathered through this methodology
Summary
According to a United Nations [1] report, it is estimated that 68% of all people will live in urban areas by 2050. The report [1] shows that there was an exponential increase in urban living from 1950 to 2018, from 751 million to 4.2 billion people. Bibri and Krogstie [2] argue that 70% of the world’s natural resources are used in urban cities, resulting in environmental destruction, degradation of ecosystems, and problems with energy resources, among others. According to Marsal-Llacuna et al [9], smart cities (SC) seek to provide high-quality services to their citizens, improve the quality of life, provide better public services, encourage innovative business, monitor and optimize urban infrastructure, preserve the environment, etc
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