Litcius/Paper detail

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

Muhammad Umair Hassan, Asma Kanwal, Muath Jarrah, Manas Ranjan Pradhan, Arshad Hussain, Beenu Mago

20222022 International Conference on Business Analytics for Technology and Security (ICBATS)25 citationsDOI

Abstract

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.

Topics & Concepts

Computer scienceExtreme learning machineNetwork congestionDeep learningArtificial intelligenceTraffic congestionTraffic flow (computer networking)Smart cityIntelligent transportation systemControl (management)Floating car dataMachine learningComputer networkComputer securityEngineeringTransport engineeringArtificial neural networkInternet of ThingsNetwork packetMachine Learning and ELMAdvanced Memory and Neural ComputingBrain Tumor Detection and Classification