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Smart city article details

Title	An Architecture And Review Of Intelligence Based Traffic Control System For Smart Cities
ID_Doc	7619
Authors	Kommineni M.; Baseer K.K.
Year	2024
Published	EAI Endorsed Transactions on Energy Web, 11
DOI	http://dx.doi.org/10.4108/ew.4964
Abstract	City traffic congestion can be reduced with the help of adaptable traffic signal control system. The technique improves the efficiency of traffic operations on urban road networks by quickly adjusting the timing of signal values to account for seasonal variations and brief turns in traffic demand. This study looks into how adaptive signal control systems have evolved over time, their technical features, the state of adaptive control research today, and Control solutions for diverse traffic flows composed of linked and autonomous vehicles. This paper finally came to the conclusion that the ability of smart cities to generate vast volumes of information, Artificial Intelligence (AI) approaches that have recently been developed are of interest because they have the power to transform unstructured data into meaningful information to support decision-making (For instance, using current traffic information to adjust traffic lights based on actual traffic circumstances). It will demand a lot of processing power and is not easy to construct these AI applications. Unique computer hardware/technologies are required since some smart city applications require quick responses. In order to achieve the greatest energy savings and QoS, it focuses on the deployment of virtual machines in software-defined data centers. Review of the accuracy vs. latency trade-off for deep learning-based service decisions regarding offloading while providing the best QoS at the edge using compression techniques. During the past, computationally demanding tasks have been handled by cloud computing infrastructures. A promising computer infrastructure is already available and thanks to the new edge computing advancement, which is capable of meeting the needs of tomorrow's smart cities. © 2024 M. Kommineni et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0. All Rights Reserved.
Author Keywords	Energy Saving; Offloading Decisions; QoS; Signal timing; Smart Cities; Traffic flow

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