vivek.mohan

The concept of Big Data is at the forefront of new technology in rail freight sector. Analytics based on Big Data is a new field in the transportation sector which presents challenges to implement & the opportunities to gain from the Big Data based analytics in terms of better preventive & predictive Asset maintenance activities. The Indian Railways has been in the last ten years implemented various condition monitoring mechanisms for its fleet of Freight wagons like Wheel Impact Load Detector (WILD), Hot Box Detector (HBD), Online Monitoring of Rolling Stock (OMRS)   &  RFID tags for wagons. All these packages will help to improve the service availability & enhanced maintenance periodicity. Mostly the data generated is used to give maintenance alerts. Data is also generated at the maintenance points while the maintenance is being undertaken & periodic checking at the en route stations. Most of this data is now available in digital form & can be utilized for gaining predictive insights.

Big Data can be defined as data so huge which is beyond the normal computing capacity available. The volume can be several GBs per day. Big data can be characterized by several attributes called as the Vs of Big Data : Volume, Variety, Veracity, Valence , Velocity & Value.

 A basic Big Data model works towards acquiring, pre processing, analyzing & getting insights from the various streams of data which is being generated by various sources- Machines, People & Organizations in the ambit of Indian Railways. Each of this step is a major step involving various iterations with a single objective of getting Actionable Insights from the torrents of data.

      These insights will be valuable for the Indian Railways in achieving high standards of serviceability, key decisions related to the sufficiency of new technology, increasing the modal share, optimization of the available infrastructure for freight maintenance & prepare a course of action for the heavy haul traffic.