Preprint Concept Paper Version 1 Preserved in Portico This version is not peer-reviewed

Smart City Data Science: Towards Data-Driven Smart Cities with Open Research Issues

Version 1 : Received: 4 April 2022 / Approved: 6 April 2022 / Online: 6 April 2022 (11:35:15 CEST)

A peer-reviewed article of this Preprint also exists.

Sarker, I. H. Smart City Data Science: Towards Data-Driven Smart Cities with Open Research Issues. Internet of Things, 2022, 19, 100528. https://doi.org/10.1016/j.iot.2022.100528. Sarker, I. H. Smart City Data Science: Towards Data-Driven Smart Cities with Open Research Issues. Internet of Things, 2022, 19, 100528. https://doi.org/10.1016/j.iot.2022.100528.

Abstract

Cities are undergoing huge shifts in technology and operations in recent days, and `data science' is driving the change in the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR). Extracting insights or actionable knowledge from city data and building a corresponding data-driven model is the key to making a city system automated and intelligent. Data science is typically the study and analysis of actual happenings with historical data using a variety of scientific methodology, machine learning techniques, processes, and systems. In this paper, we concentrate on and explore ``Smart City Data Science", where city data collected from various sources like sensors and Internet-connected devices, is being mined for insights and hidden correlations to enhance decision-making processes and deliver better and more intelligent services to citizens. To achieve this goal, various machine learning analytical modeling can be employed to provide deeper knowledge about city data, which makes the computing process more actionable and intelligent in various real-world services of today's cities. Finally, we identify and highlight ten open research issues for future development and research in the context of data-driven smart cities. Overall, we aim to provide an insight into smart city data science conceptualization on a broad scale, which can be used as a reference guide for the researchers, professionals, as well as policy-makers of a country, particularly, from the technological point of view.

Keywords

Smart cities; data science; machine learning; Internet of Things; data-driven decision making; intelligent services; cybersecurity

Subject

Computer Science and Mathematics, Information Systems

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.