Abstract
In this paper, we propose a new traffic system recommendation based on support real-time flows in highly unpredictable sensor network environments. The approach system is real-time recommendation system which meet various demands of users. The proposed algorithm include two phases. First phase is proposed to deal with the real-time problem. By this way, the drivers are able to transfer on the way with the shortest-time. For second phase, a research algorithm based on Depth First Search (DFS) algorithm will recommend the paths which meet demands of drivers based their context such as the paths with include the famous landscapes or the paths where they can find out good restaurants for their break while driving.
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Acknowledgement
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2014R1A2A2A05007154). Also, this research was supported by the MSIP Ministry of Science, ICT and Future Planning), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2015-H8501-15-1018) supervised by the IITP(Institute for Information and communications Technology Promotion).
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Bui, KH.N., Pham, X.H., Jung, J.J., Lee, OJ., Hong, MS. (2016). Context-Based Traffic Recommendation System. In: Vinh, P., Alagar, V. (eds) Context-Aware Systems and Applications. ICCASA 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 165. Springer, Cham. https://doi.org/10.1007/978-3-319-29236-6_13
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DOI: https://doi.org/10.1007/978-3-319-29236-6_13
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