Smart City Intelligent Traffic Control for Connected Road Junction Congestion Awareness with Deep Extreme Learning Machine

Congestion-free traffic management has been a top priority for Machine Learning (ML) in the smart city sector for the past decade. Machine learning Algorithms are superfluous although working with the increased amount of data but these improve the capability and intelligence at a level cost. In this research, we propose a model based on a deep learning framework with a multi-layer Extreme Learning Machine (ELM) is proposed considering congestion information at all possible connection points to smooth a signal working over that recorded information. A more desirable outcome will be achieved by the proposed method, and traffic flow and congestion will improve.