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Smart city article details

Title Emerging Data Driven Smart City And Its Solutions For Sustainability: The Case Of Cuenca-Ecuador
ID_Doc 22752
Authors Villao D.; Pérez M.; Linzan S.; Tumbaco M.
Year 2023
Published Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14108 LNCS
DOI http://dx.doi.org/10.1007/978-3-031-37117-2_12
Abstract The rapid urban growth of cities has produced several economic, social and environmental problems. This has brought the need to seek alternatives to develop more sustainable, resilient and equitable cities. One of the models that present one of the solutions for these sustainability problems are data driven sustainable smart cities, which are smart cities that use big data to generate a large amount of information that once it has been collected, stored, processed, and analyzed by different institutions with technical and specific competencies, implement actions to achieve their sustainability. Although there is no extensive literature on the characteristics of these cities, there is a theoretical framework that explains the characteristics of this type of cities. The objective of this paper is to identify the potential of the city of Cuenca in Ecuador to become a data driven sustainable smart city using this theoretical framework. The research is descriptive using the city of Cuenca as a case study, for which different sources of secondary information such as public documents about the city were used. As a result, it was identified that the city of Cuenca uses sensors to monitor traffic, air quality and noise, the implementation of smart lighting systems and the creation of a digital platform to improve the management of public services such as water, electricity and garbage collection, which makes it fit in certain characteristics to the model of a data driven sustainable smart city. However, one the main factors to fit the data driven sustainable city is the national and local context of a city. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Author Keywords Big Data; Data Driven; Smart City; Sustainability


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