Publication Type : Book Chapter
Publisher : Advances in Intelligent Systems and Computing, Springer Verlag .
Source : Advances in Intelligent Systems and Computing, Springer Verlag, Volume 398, p.331-344 (2016)
Keywords : Developing countries, Forecasting, Motor transportation, Navigation systems, Ontology, Parallel processing, Road network, Roads and streets, Rule inference, Semantic Web, Semantic Web technology, Traffic congestion, Transportation, Vehicle navigation system, video data, Video recording, Video signal processing
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2016
Abstract : In developing countries, traffic in a road network is a major issue. In this paper we investigate the tradeoff between speed versus accuracy of predicting the severity of road traffic congestion. The timely prediction of traffic congestion using semantic web technologies that will be helpful in various applications like better road guidance, vehicle navigation system. In the proposed work, ontology is created based on sensor and video data. By using rule inference of ontology on parallel processing of sensor and video data, our system gives the timely prediction of traffic congestion. © Springer India 2016.
Cite this Research Publication : Prathilothamai M., Marilakshmi, S., Majeed, N., and Viswanathan, V., “Timely prediction of road traffic congestion using ontology”, in Advances in Intelligent Systems and Computing, vol. 398, Springer Verlag, 2016, pp. 331-344.