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Smart city article details

Title	Blockchain And Machine Learning For Intelligent Traffic Management Systems In Urban Planning
ID_Doc	12378
Authors	Raj V.H.; Reddy Y.M.; Danghi P.S.; Thethi H.P.; Muhsen M.; Praveen
Year	2024
Published	Proceedings - 2024 13th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2024
DOI	http://dx.doi.org/10.1109/CSNT60213.2024.10545848
Abstract	Managing traffic and urban development in today's densely populated cities is becoming more difficult. Fortunately, there is hope in the form of a novel approach to problem solving: the combination of blockchain and machine learning. This article delves at the potential of combining blockchain technology with machine learning for use in Smart City Intelligent Traffic Management Systems (ITMS). With blockchain technology, data can be managed safely and openly, allowing for authenticated, near-real-time monitoring of traffic data. Thus, the accuracy of traffic management data is improved, and the possibility of manipulation is reduced. Algorithms in machine learning enable data analysis and predictive analytics. Large-scale traffic data analysis can optimize traffic patterns to improve urban mobility. This article examines how machine learning and blockchain technology may complement each other. This study examines the benefits of the two technologies and how their combination strengthens IT management systems. The research also examines possible issues and benefits of a holistic approach. This innovative combination of technologies can improve urban traffic management and quality of life by improving data security, traffic forecast accuracy, and urban planning efficiency. © 2024 IEEE.
Author Keywords	Adaptive Control; Blockchain; Congestion Management; Data Integrity; Intelligent Routing; Machine Learning; Sustainable Mobility; Traffic Flow; Urban Planning; Vehicle Optimization

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