Ashwini Ashok Phadtare, Khairmode Pooja S., Nikam Priyanka V., Lokhande Snehal B.


Railway systems in mega-cities are affected by various events such as natural disasters, accidents, and public gatherings. In 2017 near Manikpur railway station in Uttar Pradesh killing three and injuring at least nine passenger because of the thirteen coaches of Vasco Da Gama-Patna Express derailed. A huge and complicated networks in the railway system increase uncertainty in the network because they provides various transfer routes to passenger. Visualization is one of the most important techniques for examining such unnecessary situations in the large networks. In this paper, we proposed a new approach for visual integration of traffic analysis and social media analysis using two forms of big data: railway station data and social media data like SMS service. In that we present different views to usually and simultaneously explore changes in passenger flow and abnormal situations extract from railway station data and situational explanations of passenger such as complaints about services extracted from social media. It exhibits the possibilities and usefulness of our visualization environment using a dataset studies and experts feedback about various kinds of events.


Visual analysis, Information visualization, Data mining, big data, Railway station data, Social media data.

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