Indian Railways (IR) has entered into a collaborative pact with Indian School of Business (ISB) for setting up a Centre of Excellence for Artificial Intelligence and Data Analytics at the South Central Railway (SCR).
Vinod Kumar Yadav, Chief Executive Officer and Chairman, Railway Board, said on Thursday that the establishment of the Centre of Excellence in Artificial Intelligence and Data Analytics “is a very important step forward in the transformation of Indian Railways”.
Railways has already digitised almost all of its systems like passenger reservations, freight operations, material management, stores procurement and human resource development, among others.
“It is essential that all the data gathered is analysed for the betterment of customer services and for provision of better services to both passenger and freight customers,” Yadav said.
Indian Railways is looking to use Artificial Intelligence (AI) and Data Analytics (DA) in partnership with ISB for innovative solutions.
Gajanan Mallya, General Manager, SCR, said with increasing importance being given to DA and AI, it was the “right time” for the establishment of a Centre of Excellence (CoE).
Milind Sohoni, Deputy Dean, ISB, Hyderabad, said the vast data generated by the Railways will be used for strengthening the Railways through the application of AI and DA, he added.
This collaboration with ISB for establishing the CoE in AI and DA at SCR is for 12 months during which projects will be undertaken for improving operational efficiencies.
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The training modules will include cloud computing, data science, Big Data Analytics, AI using reinforced learning and various other techniques to be used for forecasting and prediction. ISB will further help in identifying the best global practices in AI and DA for adoption in Railways.
ISB will help identify areas for improving operational efficiencies and enhancing customer experience through application of AI and analytics.
AI and DA technologies can help Railways enhance customer engagement, allowing the Railways to deliver on customers’ growing expectations ― predicting, pre-empting and resolving faster and better than ever.
Demand data (seasonal/local) will be captured, which can help predict future demand patterns, besides in optimal utilisation of resources and cost control by weeding out ineffective/inefficient resources, according to a release.