Data Mining for Traffic Prediction and Analysis using Big Data
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2017 by IJETT Journal|
|Year of Publication : 2017|
|Authors : Rahul Khokale, Ashwini Ghate
|DOI : 10.14445/22315381/IJETT-V48P227|
Rahul Khokale, Ashwini Ghate "Data Mining for Traffic Prediction and Analysis using Big Data", International Journal of Engineering Trends and Technology (IJETT), V48(3),152-156 June 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Today we are living in a data-driven world. Developments in data generation, gathering and storing technology have empowered organizations to gather data sets of massive size. Data mining is a term that blends traditional data analysis methods with cultured algorithms to handle the tasks stood by these new forms of data sets. This paper is a comparative analysis of various Data Mining of traffic data using big data, visualization and data mining techniques to predict and analyse traffic. Wireless sensor networks are a technology which has played a massive role enabling a Smarter City cities is using this technology to gather data related to traffic. The objective is to have a complete infrastructure that enable the monitoring of traffic behaviours so decisions on city development can be made in a smarter way. The work exploring the application of data mining tools to support in the progress of traffic signal judgement devices. The cluster analysis approach is able to apply a high-resolution system state description that takes advantage of the wide-ranging set of sensors arranged in a traffic signal system.
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