Smart cities connect people and places using innovative technologies such as Data Mining
(DM), Machine Learning (ML), big data, and the Internet of Things (IoT). This paper presents …

Abstract Machine Learning (ML) algorithms can analyze large amounts of traffic data, learn
from patterns and past behaviors, and provide insights into the current and future traffic flow …

Ever since the first cities were created, they have been dependent on technology to sustain
life. The smart city paradigm integrates advanced monitoring, sensing, communication, and …

In the light of the adverse effects of climate change, data analysis and Machine Learning
(ML) techniques can provide accurate forecasts, which enable efficient scheduling and …

As cities continue to grow and the number of vehicles on the road increases, traffic
congestion and pollution have become major issues. Fortunately, significant efforts have …

In this study, we review articles published in academic journals. in the last 5 years at the
intersection of big data and the smart city context. Based on a dataset of 192 articles, we use …

In the modern world of urbanization, the needs of any smart city are to manage the various
important wheels of the city like water and electricity, urban transportation and traffic system …

Congestion in large and growing cities is a significant issue that harms the economy,
travelers, and the ecosystem. Forecasting the degree of congestion on a road network in …

Traffic congestion in major cities is becoming increasingly severe. Numerous academic and
commercial initiatives were conducted over the past decades to address this challenge …

To address the limitations in precision of conventional traffic state estimation methods, this
article introduces a novel approach based on the Transformer model for traffic state …