Smart City Gnosys

Smart city article details

Title	Short-Term Traffic Flow Prediction Of The Smart City Using 5G Internet Of Vehicles Based On Edge Computing
ID_Doc	48710
Authors	Zhou S.; Wei C.; Song C.; Pan X.; Chang W.; Yang L.
Year	2023
Published	IEEE Transactions on Intelligent Transportation Systems, 24, 2
DOI	http://dx.doi.org/10.1109/TITS.2022.3147845
Abstract	The paper aims to explore the performance of short-term traffic flow prediction of the 5G (5th Generation Mobile Communication Technology) Internet of Vehicles (IoV) based on edge computing (EC) for the smart city and to further improve the intelligence of the smart city. Aiming at the current emergency of traffic congestion and road congestion, the present work adds EC to the current vehicle network, and integrates a deep convolution random forest neural network (DCRFNN). Additionally, it implements a model for short-term traffic flow prediction of a 5G vehicle network based on EC and deep learning (DL), and analyzes its performance by simulation. The results reveal that the proposed algorithm has a lower average delay cost, and the average unloading utility is stable at approximately 70%. In the prediction performance analysis, the recognition accuracy of the proposed algorithm reaches 98.06%. It is at least 1.14% higher than that of the advanced convolution neural network (CNN) algorithm proposed by other scholars and achieves a faster convergence rate. Therefore, the constructed short-term traffic prediction model implemented has a high-quality prediction performance while also ensuring a better unloading performance. The results can provide an experimental basis for traffic flow prediction and intelligent development of the smart city. © 2000-2011 IEEE.
Author Keywords	5G Internet of Vehicles; Edge computing; smart city; traffic flow; unloading

Similar Articles

Id	Similarity	Authors	Title	Published
21773	0.945	Parveen Banu S.; Patil Y.M.; Somasundaram R.; Santhosh C.; Singh D.P.; Manikandan G.	Edge Computing-Based Short-Term Traffic Flow Forecast For The Smart City Employing 5G Internet Vehicles	Proceedings of International Conference on Contemporary Computing and Informatics, IC3I 2024 (2024)
31654	0.906	Negi S.K.; Sharma S.; Chandra P.K.	Innovations To Enhance Traffic Prediction And Empowering Iov For Smart Cities	ESIC 2025 - 5th International Conference on Emerging Systems and Intelligent Computing, Proceedings (2025)
15826	0.904	Yu M.	Construction Of Regional Intelligent Transportation System In Smart City Road Network Via 5G Network	IEEE Transactions on Intelligent Transportation Systems, 24, 2 (2023)
8075	0.901	Zheng G.; Chai W.K.; Katos V.	An Ensemble Model For Short-Term Traffic Prediction In Smart City Transportation System	Proceedings - IEEE Global Communications Conference, GLOBECOM (2019)
35879	0.9	Chaymae T.; Mhamed R.; Soumia Z.	Machine Learning And 5G Edge Computing For Intelligent Traffic Management	International Journal of Advanced Computer Science and Applications, 16, 6 (2025)
1395	0.898	Tripathi A.N.; Sharma B.	A Deep Review: Techniques, Findings And Limitations Of Traffic Flow Prediction Using Machine Learning	Lecture Notes in Mechanical Engineering (2023)
35257	0.893	Ateya A.A.; Soliman N.F.; Alkanhel R.; Alhussan A.A.; Muthanna A.; Koucheryavy A.	Lightweight Deep Learning-Based Model For Traffic Prediction In Fog-Enabled Dense Deployed Iot Networks	Journal of Electrical Engineering and Technology, 18, 3 (2023)
11489	0.885	Mohammed G.P.; Alasmari N.; Alsolai H.; Alotaibi S.S.; Alotaibi N.; Mohsen H.	Autonomous Short-Term Traffic Flow Prediction Using Pelican Optimization With Hybrid Deep Belief Network In Smart Cities	Applied Sciences (Switzerland), 12, 21 (2022)
48697	0.885	Bilotta S.; Collini E.; Nesi P.; Pantaleo G.	Short-Term Prediction Of City Traffic Flow Via Convolutional Deep Learning	IEEE Access, 10 (2022)
7021	0.884	Qaffas A.A.	Ai-Driven Distributed Iot Communication Architecture For Smart City Traffic Optimization	Journal of Supercomputing, 81, 8 (2025)