Data Science Process for Smart Cities

Abstract

Smart cities have been proposed as information technology strategies to generate solutions for the benefit of large cities to improve their quality of life, through phenomena identification tools that use artificial intelligence. Some work has been aimed at developing the infrastructure for monitoring events and the Internet of things, others merely on data analytics without an application system context. This work cites various investigations on data science processes of the smart cities and reports some of its works whose main topics are planning for the start of a smart city, the framework for the analysis of smart cities, and smart cities big data algorithms for sensors location. In these cases, the experiences in these cases are described as well as the trend towards a new process with the form of monitoring-analysis-evaluation-found pattern-driving object-decision-making and the future of smart cities is finally discussed.

Digital transformation in transport infrastructure energy efficiency: Smart cities and sustainable mobility

“…In the contemporary landscape characterized by burgeoning environmental challenges and mounting demands for the efficacious management of resources, the transport sector emerges as an area of strategic significance for digital transformation, one that holds the potential to make a substantial contribution toward the enhancement of energy efficiency and the sustainability of transport infrastructure. The comprehension and scrutiny of the digital transformation occurring within the industry constitute pivotal components in the formulation of strategies aimed at ameliorating energy efficiency and guaranteeing the sustainability of mobility in the present-day intelligent urban environments [1].…”