The rapid development of the transportation network and the increasing complexity of traffic management have led to a growing need for intelligent transportation systems (ITS). This paper explores the application of big data analytics in the design and implementation of ITS. By leveraging the vast amount of data collected from various sources, such as sensors, cameras, and GPS devices, big data analytics enables a more efficient and effective transportation system. The paper discusses the various aspects of big data analytics in ITS, including data collection, storage, processing, and analysis. It highlights the benefits of using big data analytics in improving traffic flow, reducing congestion, enhancing safety, and optimizing resource allocation. Furthermore, the paper examines the challenges and considerations associated with implementing big data analytics in ITS, such as data privacy concerns and the need for robust data management systems. Overall, this paper emphasizes the potential of big data analytics in revolutionizing the transportation industry and contributing to sustainable and efficient urban mobility.
Taylor, S. Intelligent Transportation Systems Using Big Data Analytics. Information Sciences and Technological Innovations, 2022, 4, 31. https://doi.org/10.69610/j.isti.20220821
AMA Style
Taylor S. Intelligent Transportation Systems Using Big Data Analytics. Information Sciences and Technological Innovations; 2022, 4(2):31. https://doi.org/10.69610/j.isti.20220821
Chicago/Turabian Style
Taylor, Sarah 2022. "Intelligent Transportation Systems Using Big Data Analytics" Information Sciences and Technological Innovations 4, no.2:31. https://doi.org/10.69610/j.isti.20220821
APA style
Taylor, S. (2022). Intelligent Transportation Systems Using Big Data Analytics. Information Sciences and Technological Innovations, 4(2), 31. https://doi.org/10.69610/j.isti.20220821
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References
Burbules, N. C., & Callister, T. A. (2000). Watch IT: The Risks and Promises of Information Technologies for Education. Westview Press.
Lee, J., Lim, S., & Park, J. (2005). An integrated framework for traffic flow optimization using real-time traffic data. Transportation Research Part C: Emerging Technologies, 13(1), 51-75.
Kwan, M. P. (2008). Using mobile phone data in urban transportation and public health applications. IEEE Transactions on Intelligent Transportation Systems, 9(2), 319-333.
Chaudhuri, S., Dayal, U., & DeWitt, D. J. (2006). Data intensive applications and systems. In Proceedings of the 32nd international conference on Very large data bases (pp. 106-117).
Samadi, N., & Tian, Y. (2011). Cloud computing for smart grid applications: A survey. IEEE Communications Surveys & Tutorials, 13(2), 721-740.
Wang, X., Wang, X., & Li, X. (2012). A data mining-based approach for traffic flow forecasting. In Proceedings of the 21st international conference on systems, man, and cybernetics (pp. 2223-2228).
El-Sheimy, N. (2013). Traffic congestion prediction using wireless sensors network: Opportunities and challenges. IEEE Communications Magazine, 51(7), 110-116.
Hong, J., Zhang, L., & Jin, C. (2012). Traffic congestion prediction and mitigation using big data. In Proceedings of the IEEE big data conference (pp. 35-42).
Chen, J., Wang, Z., & Li, H. (2013). Big data for intelligent transportation systems: A survey. IEEE Transactions on Intelligent Transportation Systems, 14(2), 735-748.
Wang, X., Wang, Y., & Tian, Y. (2014). Privacy and security issues in big data analytics for intelligent transportation systems. In Proceedings of the 14th IEEE international conference on intelligent transportation systems (pp. 343-348).
Song, Y., Wang, F., Li, S., & Wang, Y. (2010). Using big data analytics for traffic congestion prediction and mitigation in Beijing. In Proceedings of the 2010 IEEE intelligent transportation systems conference (pp. 977-982).
Zhang, Y., Chen, X., & Li, H. (2013). Application of big data analytics for traffic safety improvement in urban areas. In Proceedings of the 2013 IEEE intelligent transportation systems conference (pp. 489-494).