Sabiha Gökçen: measuring the crowd and answering its questions
Sabiha Gökçen's passenger-flow sensors and SAVVy assistant work on two different sources of passenger friction: congestion inside the terminal and uncertainty about the airport.
Sabiha Gökçen International Airport, Istanbul, August 2024. Photograph: Apaleutos25 / CC BY-SA 4.0 (cropped to fit). Shows the airport, not an AI implementation.
The picture at Istanbul Sabiha Gökçen
Crowding and uncertainty are not the same problem
Passenger density can change quickly at security and other processing points. Sabiha Gökçen uses Xovis passenger-tracking technology, with the supplier describing 184 AI-enabled sensors to monitor how the terminal is being used.
The SAVVy digital assistant, reported in May 2026, answers passenger questions through web, mobile and WhatsApp channels. The assistant may reduce unnecessary enquiries, but its success cannot be inferred from sensor coverage or website availability.
The airport's two recorded deployments therefore offer complementary but separate measures of passenger experience.
Selected implementations
Information for airport staff and passengers
01 / Deployed
Seeing where the queue is forming
The operational problem
Operational staff need a reliable estimate of congestion before a terminal bottleneck becomes disruptive.
What the sources report
Xovis described its Passenger Tracking System installation with airport partners, including 184 AI-enabled sensors at Sabiha Gökçen.
Why it matters
Measurements may help teams position staff and advise travellers if the system is used in live decisions.
What remains unproven
Queue-forecast accuracy, coverage by processing stage and improvements in waiting time are not independently established.
Evidence supports a reported claim; it does not automatically establish a measured operating benefit.
The wider register
What else is happening at Istanbul Sabiha Gökçen?
These two deployments account for the current public register at this airport; further findings should be attached to the appropriate function rather than creating artificial categories.
No additional publicly listed deployment records.
Two tasks, two scorecards
Passenger-flow sensing can be tested against observed queues and staffing choices. SAVVy can be tested against correct answers and resolved questions.
Until such results are available, the published evidence supports deployment, not a quantified improvement in passenger experience.
Live data from the Aerostack register. Status reflects published evidence only. See Our approach for how records are graded.
Aerostack register · 2 tracked deployments
Aerostack tracks AI deployments across airports and airlines, with the published evidence behind each record. Photography is real aviation imagery. Record thumbnails may show the named airport or airline; other photographs do not.
