Deep learning (DL) and machine learning (ML) methods have recently contributed to the
advancement of models in the various aspects of prediction, planning, and uncertainty …

Deep learning (DL) and machine learning (ML) methods have recently contributed to the
advancement of models in the various aspects of prediction, planning, and uncertainty …

The fast development of metropolitan communities around the globe has created new issues
for individuals' everyday life, such as contamination, community safety, and traffic …

The development in our urban cities has increased significant risks with everyday lives, like
traffic congestion, pollution of the atmosphere, energy use, and public safety among others …

The manuscript represents a comeprehensive and systematic literature review on the
machine learning methods in the emerging applications of the smart cities. Application …

Abstract Machine Learning (ML) and Deep Learning (DL) methods have contributed to the
progression of models in the different aspects of planning, prediction, and uncertainty …

Following the evolution of big data collection, storage, and manipulation techniques, deep
learning has drawn the attention of numerous recent studies proposing solutions for smart …

Smart Cities utilize Information and Communication Technology (ICT) tools to improve
operational efficiency and provide excellent service. It aims to make the core infrastructure …

Purpose The purpose of this paper is to propose a distributed deep learning architecture for
smart cities in big data systems. Design/methodology/approach We have proposed an …

The purpose of smart city is to enhance the optimal utilization of scarce resources and
improve the resident's quality of live. The smart cities employed Internet of Things (IoT) to …