The fog season over Northern India in winter, especially at Indira Gandhi International (IGI) Airport in Delhi, had been a debilitating operation hurdle for aviation in the country. These low-visibility conditions (LVPs) require flights to be cancelled and diverted, leading to huge delays that cause a chain reaction of chaos stranding thousands of passengers and costing airlines millions.
But the days of counting entirely on reactive measures and praying for good weather are numbered. A major transformation is taking place where IGI Airport and leading carriers such as IndiGo are evolving to using advanced technologies like Artificial Intelligence (AI), enabling them to rise above fire-fighting, reactive approaches of day-today operations management to being ahead of time in views of future forecast. The aim of this technological leap forward is more efficient movement and a safer travel experience even when visibility dips to almost nil.
How artificial intelligence is changing travel: ai at the heart of the airport
The largest AI battle against the fog is being waged at the airport level, that’s IGI’s Airport Predictive Operations Centre (APOC). This core is the functional heart, technologically marrying and analyzing stupendous quantities of data on-the-fly.
Here’s a basic primer on how the APOC works, and what it brings to bear: The APOC system operates by taking in a rich mix of information:
Meteorological Information: From a set of sensors in the airports with information of LIDARs, and ceilometers that record the height of fog, visibility, temperature and dew point.
Predictive Weather Models: High-level forecasting to 36 hours in advance, with especial emphasis on data drawn from the WiFEX (Winter Fog Experiment) project for predicting dense fog.
Airside Input Operations: Describes the runway usage, gate availability and aircraft sequencing information.
By using these streams in combination, the APOC can predict with AI algorithms not merely whether there will be fog but when that fog will roll over various sections of the airfield and how long it is likely to linger. This predictive capability makes possible faster decisions and much more accurate resource allocation based on a traditional, static operational plan.
Proactive Roster Management and Crew Optimisation at IndiGo
Fog leads to a snowball effect for airlines such as IndiGo — which had clear skies on three out of every four days this December but operates a complex web of high-frequency flights. A single delayed flight in Delhi can then distrupt dozens of other subsequent connections across the country. Outside of this, IndiGo is applying data-driven approaches that are focused on the management of its crew and operations readiness.
The integrated OCC at IndiGo uses sophisticated tools to:
IndiGo utilises analytics to roster these highly-skilled crews in advance on flights that are susceptible to being affected by fog, enabling even more operations safely taking off and landing during low-visibility periods (LVPs).
Active FDTL Management: The Flight Duty Time Limitations (FDTL), the new set of rules that control how long a pilot can rest and for how long a pilot can work are, during fog episodes, one of the limiting factors. AI tools also assist the OCC to enforce crew compliance with its rules in real-time, avoiding a cascade of holds from pilots timing out as they wait for weather clearance.
Pre-Positioning of Resources: Informed by AI based fog predictions, the airline can arrange accommodation and transport for its crew members in advance near key fog susceptible airports. This prevents the crew from being on-hold as soon as visibility returns).
By using these tools to predict crew availability issues and by tying resources to advanced weather predictions, IndiGo is changing its winter plan from crisis management driven by the situation at hand (or in the air) to the proactive avoidance of risk.
In the end, it’s a collaboration between technology and human teamwork to combat the winter whiteout. The airport’s and major carriers like IndiGo’s embracing of AI represents an ongoing commitment to operational resilience – one that is likely to result in Indian passengers enjoying a much smoother, less stressed travel experience during the challenging winter season.
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