Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/76958
Title: Big data analytics for smart transportation
Authors: Lee, Alvin Yong Teck
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2019
Abstract: In today's technologically advanced world, almost everything revolves around data. As technology advances, the amount of data also grows at a rapid pace. Big data has helped many institutions to gain valuable insights on various aspects to aid them in better decision making. Urban traffic analysis is crucial for traffic forecasting systems, urban planning and, more recently, various mobile and network applications. Hence, by analysing big data with urban traffic, the types and frequencies of vehicles activity can be identified. As a result, the analysed data can be used to enhance traffic planning of a nation. The project followed a series of steps to form the traffic visualization system structure. Firstly, the system conducted a data cleaning of the raw data provided by the Land Transport Authority (LTA). Secondly, the data would be formulated by performing map matching before storing the data into MySQL. Thirdly, the data would be analysed by going through a formula to derive an estimate of the traffic condition. Lastly, the analysed data would be visualized on the Graphical User Interface (GUI) with optimal performance and efficiency. As a result, this will provide informative traffic conditions for the end users.
URI: http://hdl.handle.net/10356/76958
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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