Smart City Gnosys

Smart city article details

Title	Enhancing Urban Traffic Management Through Real-Time Anomaly Detection And Load Balancing
ID_Doc	24079
Authors	Laanaoui M.D.; Lachgar M.; Mohamed H.; Hamid H.; Villar S.G.; Ashraf I.
Year	2024
Published	IEEE Access, 12
DOI	http://dx.doi.org/10.1109/ACCESS.2024.3393981
Abstract	Efficient traffic management has become a major concern within the framework of smart city projects. However, the increasing complexity of data exchanges and the growing importance of big data makes this task more challenging. Vehicular ad hoc networks (VANETs) face various challenges, including the management of massive data generated by different entities in their environment. In this context, a proposal is put forth for a real-time anomaly detection system with parallel data processing, thereby speeding up data processing. This approach accurately computes vehicle density for each section at any given time, enabling precise traffic management and the provision of information to vehicles regarding traffic density and the safest route to their destination. Furthermore, a machine learning-based prediction system has been developed to mitigate congestion problems and reduce accident risks. Simulations demonstrate that the proposed solution effectively addresses transportation issues while maintaining low latency and high precision. © 2013 IEEE.
Author Keywords	intelligent transportation systems; real-time anomaly detection; traffic density prediction; Urban traffic management

Similar Articles

Id	Similarity	Authors	Title	Published
12135	0.949	Tantaoui M.; Moukhafi M.; Chana I.	Big Data Vehicle Density Management In Vehicular Ad-Hoc Network	Indonesian Journal of Electrical Engineering and Computer Science, 33, 1 (2024)
57989	0.904	Tantaoui M.; Laanaoui M.D.; Kabil M.	Towards An Efficient Vehicle Traffic Management Using Big Data	ACM International Conference Proceeding Series (2019)
36035	0.898	Bawaneh M.; Simon V.	Machine Learning-Based Anomaly Detection In Smart City Traffic: Performance Comparison And Insights	International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS - Proceedings (2025)
55926	0.898	Mahmoudian M.; Zanjani S.M.; Shahinzadeh H.; Kabalci Y.; Kabalci E.; Ebrahimi F.	The Intelligent Mechanism For Data Collection And Data Mining In The Vehicular Ad-Hoc Networks (Vanets) Based On Big-Data-Driven	Proceedings - 2023 IEEE 5th Global Power, Energy and Communication Conference, GPECOM 2023 (2023)
9607	0.893	Islam J.; Talusan J.P.; Bhattacharjee S.; Tiausas F.; Vazirizade S.M.; Dubey A.; Yasumoto K.; Das S.K.	Anomaly Based Incident Detection In Large Scale Smart Transportation Systems	Proceedings - 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022 (2022)
1276	0.89	Wilbur M.; Dubey A.; Leao B.; Bhattacharjee S.	A Decentralized Approach For Real Time Anomaly Detection In Transportation Networks	Proceedings - 2019 IEEE International Conference on Smart Computing, SMARTCOMP 2019 (2019)
30762	0.883	Ali Shah S.A.; Fernando X.; Kashef R.	Improved Vehicular Congestion Classification Using Machine Learning For Vanets	SysCon 2024 - 18th Annual IEEE International Systems Conference, Proceedings (2024)
47341	0.879	Islam M.J.; Talusan J.P.; Bhattacharjee S.; Tiausas F.; Dubey A.; Yasumoto K.; Das S.K.	Scalable Pythagorean Mean-Based Incident Detection In Smart Transportation Systems	ACM Transactions on Cyber-Physical Systems, 8, 2 (2024)
1530	0.878	Mejdoubi A.; Fouchal H.; Zytoune O.; Ouadou M.	A Distributed Predictive Road Traffic Management System In Urban Vanets	2019 15th International Wireless Communications and Mobile Computing Conference, IWCMC 2019 (2019)
31957	0.876	Guru Vimal Kumar M.; Jude Moses Anto Devakanth J.; Selvapandian D.; Venkatesan R.; Revathi J.; Aruna R.	Integrating Cloud-Based Data Mining Algorithms For Smart City Infrastructure Management And Decision Support Systems	Proceedings - 2024 4th International Conference on Soft Computing for Security Applications, ICSCSA 2024 (2024)