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Smart city article details

Title	Smart City: Road Traffic Monitoring System Based On The Integration Of Iot And Ml
ID_Doc	50657
Authors	Saini K.; Sharma S.
Year	2023
Published	Lecture Notes in Networks and Systems, 686 LNNS
DOI	http://dx.doi.org/10.1007/978-981-99-2100-3_12
Abstract	One of the critical challenges generated by globalization is managing the traffic on the roads. The mishandling of road traffic because of its varying nature hinders efficient traffic flow, consumes time, and poses a risk to road safety. All these problems can be resolved with the aid of an efficient and trustworthy smart road traffic monitoring (SRTM) system. Even though a substantial amount of study has been done on road traffic management, still it remains an active topic of research. Evolving techniques like the Internet of things (IoT) and machine learning (ML) may help in the development of an efficient and robust system for monitoring traffic. Moreover, by integrating these techniques, decision-making mechanisms can be improved, and even urban evolution can be promoted. Therefore, the primary purpose of this paper is to study the role of the Internet of things (IoT) and machine learning (ML) in smart road traffic monitoring (SRTM) scenarios independently as well as when collaborating. Further, to gain a deeper understanding of the system, several IoT and ML frameworks for road traffic management are examined including the techniques used, outcomes, and their future work also. From the comparative analysis of the frameworks, it is seen that IoT and ML when used together in traffic management prove to be much more efficient. Moreover, this paper gives only the theoretic review of the state of traffic monitoring system and not any kind of practical implementation. So, in future, IoT and ML-aided efficient framework for road traffic monitoring will be designed and implemented. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Author Keywords	Cloud computing; Edge computing; Internet of things (IoT); Machine learning (ML); Traffic monitoring

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