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Smart city article details

Title	Ai And Machine Learning For Intelligent Traffic Management In Iot-Connected Cities
ID_Doc	6910
Authors	Dankan Gowda V.; Yogi K.S.; Srinivas I.V.; Kumar B.K.; Srinivas D.; Sudhakar Reddy N.
Year	2024
Published	2024 Asian Conference on Intelligent Technologies, ACOIT 2024
DOI	http://dx.doi.org/10.1109/ACOIT62457.2024.10939299
Abstract	The paper researches the possibility of identifying a potential approach of an intelligent traffic management system worrying the feasible uses of AI & ML for Traffic management in Smart Cities under IoT technology. The nodes that make this system efficient are the ability to capture real time data from the IoT devices including the sensors as well as the cameras in order to analysis the traffic patterns and therefore has the ability to adjust the traffic signals in real time. The specific form of the artificial intelligence algorithm used in the method were machine learning models, for example, Long Short Term Memory (LSTM) networks so as to enhance the ability to predict traffic condition. The enhancement that was attained permitted rural accessibility with flow densities throughout the peak period being lowered to a quarter and the average trip duration being cut down by to one fifteenth. From the results it was revealed that with the huge amount of data and real time decision making the proposed system minimally could address the traffic problem of the urban area. Hence, this current research supports AI interventions in improving the utility of the transport systems in cities. © 2024 IEEE.
Author Keywords	AI; Connected Cities; Intelligent Traffic Management; IoT; Machine Learning; Real-Time Data Processing; Smart Transportation

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