How IGI Airport Is Using AI and Upgraded Runways to Beat Winter Fog

Delhi Airport had integrated AI-driven tools and predictive analytics to minimise fog-related disruptions. The new system had combined live data, weather models and operational inputs, allowing faster decisions and smoother coordination during low visibility.(AI image)

The Airport Predictive Operations Centre had unified all critical data into one command hub. It had helped optimise runway usage, manage aircraft sequencing and improve gate allocation, ensuring smoother operations during unpredictable fog conditions.(AI image)

The airport had equipped the Dwarka end of runway 10/28 with a CAT-III Instrument Landing System. With this upgrade, three runways had become CAT-III compliant at both ends, enabling safe landings and around 30 operations per hour even in dense fog.(AI image)

DIAL had announced that the airside enhancements were expected to cut fog-related recovery time by nearly four hours. The upgraded runways and operational planning had significantly strengthened the airport’s ability to resume services quickly after LVPs.(AI image)

The airport had begun using Winter Fog Experiment (WiFEX) data, which claimed 85% accuracy in fog prediction. This initiative had aimed to support faster planning and better preparedness for fog waves that often disrupted early-morning flight schedules.

IITM and IMD had continued collecting detailed fog-related data under the WiFEX project. This research had helped build advanced models predicting fog 1–36 hours ahead and had improved understanding of local weather behaviour around the Delhi region.(AI image)

DIAL’s CEO had said that while weather disruptions could not be eliminated entirely, the upgrades had significantly boosted the airport’s ability to plan, respond and recover. The combined tech and infrastructure push had strengthened winter readiness.