Digital Station: Capacity Forecasting

Use Case

Challenges

  • Underutilization of the rail network during off-peak hours
  • Overcrowding during rush hours
  • Lack of dynamic, live information for passengers

 

Supported Industries:

  • Smart Buildings & Construction
  • Smart Cities, Traffic & Highways
  • Transportations & Logistics

Transformation Results

  • Prediction of passenger demand and flow based on real and historical data from entry gates, ticketing, CCTV and train weight
  • Possible integration of contextual data like planned sports events or weather forecast
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Value

  • Improved service for passengers
  • Decreased dwell time and unplanned stops at stations
  • Optimized station operations and reduced expenditures
  • Adjusted transit schedules based on predicted vs. actual passenger demand
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