Recent Developments of Deep Learning in Future Smart Cities: A Review

Abstract

Urban and rural areas are adapted to address the latest technological innovations such as smart cities and concurrently arisen new opportunities for public safety to citizens and visitors. Smart cities aim to sustain the emerging urbanization, amount of energy used, conserve green living, and simultaneously help enhance people’s productivity and lifestyle. Apart from that, smart cities are the catalyst in improving people’s ability to use advanced computerized information efficiently. Deep learning (DL) and the Internet of Things (IoT) are crucial in establishing government and industrial business standards, risk management, application, and productivity output. In smart cities, several IoT sensors have been installed in a some places for public data gathering such as road traffic and people’s movement. DL is an advanced machine learning technique meant for extensively on data collection, patterns understanding, and data prediction. Besides, DL has caught the interest of every researcher around the world, and it has delivered remarkable results in comparison to the current standard techniques. This chapter aims to explore the recent development of DL techniques for the evolution of smart cities and to study the future directions.