Smart cities: the role of Internet of Things and machine learning in realizing a data-centric smart environment

TLDR

Smart cities use technology and data to improve citizen quality of life and urban service efficiency, with IoT and machine learning emerging as key enablers for large‑scale data collection, analysis, and decision‑making. The paper explores smart cities and the role of IoT and ML in creating a data‑centric smart environment, providing an overview of applications and discussing implementation challenges. It reviews smart city applications, discusses implementation challenges, and compares case studies of successful IoT and ML deployments. The study finds that IoT and ML can transform cities into more livable, sustainable, and efficient environments, but data privacy, security, and ethical challenges must be addressed.

Abstract

Abstract This paper explores the concept of smart cities and the role of the Internet of Things (IoT) and machine learning (ML) in realizing a data-centric smart environment. Smart cities leverage technology and data to improve the quality of life for citizens and enhance the efficiency of urban services. IoT and machine learning have emerged as key technologies for enabling smart city solutions that rely on large-scale data collection, analysis, and decision-making. This paper presents an overview of smart cities’ various applications and discusses the challenges associated with implementing IoT and machine learning in urban environments. The paper also compares different case studies of successful smart city implementations utilizing IoT and machine learning technologies. The findings suggest that these technologies have the potential to transform urban environments and enable the creation of more livable, sustainable, and efficient cities. However, significant challenges remain regarding data privacy, security, and ethical considerations, which must be addressed to realize the full potential of smart cities.