Bharat in Betastartup field guide
← Back to the atlas
No. 1261Problem statementMobility and logistics

Dynamic Forecast of Expected Time of Arrival (ETA) for Coaching Trains

Source

Source summary

The ETA proposal should dynamically update arrival forecasts for passenger trains from live running conditions, historical delays and downstream network constraints. Relevant inputs include GPS location, signals, sectional speeds, congestion, weather and maintenance or speed restrictions. Machine learning or statistical models should scale across thousands of trains and multiple operating zones, with APIs supplying passenger apps, station displays and control-room planning.

No. 352Problem statementMobility and logistics

Artificial intelligence in logistics and SCM

The source names AI-based logistics and supply-chain management for stores, spares and rations. It is a broad stated application area and does not identify a specific algorithm, workflow, scale or commercial model.

No. 537Problem statementMobility and logistics

Simple Artificial Intelligence Based Prediction Model for Bird Hazard Management System

The Indian Air Force wants a real-time model of bird-aircraft collision risk around target airfields. One module should estimate typical seasonal bird density from field observations, historical patterns and expert knowledge; a second should adjust forecasts for the next 24 hours to three days using live weather and remote-sensor data; a third should quantify species-level hazard from strike frequency, damage and bird mass.

No. 626Problem statementMobility and logistics

Standardisation of GCS

Standardise the Indian Army's ground-control stations across unmanned aerial vehicles. The source asks for modules that convert existing and already-planned stations into a common station usable across vehicles, plus standard conditions that future vendors must follow so later systems conform without retrofit.