Machine Learning Approaches for Smart City Applications: Emergence, Challenges and Opportunities

Abstract

Nowadays, smart cities aim to efficiently manage all sectors like growing urbanization, maintaining a green environment, energy consumption and life style of the people. The concept is to increase the capability of people to efficiently adapt and use all modern Information and Communication Technology (ICT) trends. The main effort is to increase the core infrastructure of the cities and give people an improved quality of life. The primary objective of this work is to give detailed background knowledge of Machine Learning (ML) algorithms and explores the role of ML, Deep Reinforcement Learning (DRL) and Artificial Intelligence (AI) in development of the smart city. The paper presents a comprehensive overview of smart city concept and focuses on different privacu solutions in the smart city. Further, the paper highlights the role of ML in various smart city applications such as intelligent transportation system, smart grids, healthcare, cyber security, and supply chain management. Finally, the work enumerates some future research directions to guide further advancements in the area.