Lanzhou: an operations centre built around a digital airport
Lanzhou's Terminal 3 has a joint operating centre and reported AI security functions. Published efficiency figures are striking, but their connection to individual systems needs care.
Lanzhou Zhongchuan International Airport. Photograph: Kevin Hale / CC BY-SA 2.0 (cropped to fit). Shows the airport, not an AI implementation.
The picture at Lanzhou Zhongchuan
One airport, several operating layers
Lanzhou opened its new terminal in March 2025 with a joint operations centre, digital-twin representation and systems to coordinate vehicles, stands and resources.
Its airside and terminal services include facial passenger processing and an AI security platform; regional reporting also describes robotics and bird detection. The distinction between data integration and specific AI uses matters.
Airport and state-news figures offer a view of scale, but they should not be treated as independently audited AI-attributable outcomes.
Selected implementations
The operating centre and specific AI functions
01 / Deployed
The airport appears on one operating picture
The operational problem
Coordinating airside vehicles, stands and emergency teams is difficult when their location and status are held separately.
What the sources report
CAAC News describes a digital twin combining 5G and positioning information to follow operational events, with 153 workstations in a joint operations centre. The same reporting claims faster emergency response and resource allocation.
Why it matters
A shared view can improve coordination even without proving a predictive algorithm is responsible.
What remains unproven
The efficiency figures are publisher-reported and are not isolated controlled evaluations of the digital twin's AI contribution.
Wildlife incursions can put aircraft at risk and require a rapid alert to airfield staff.
What the sources report
CAAC News describes an AI security platform that uses computer vision and machine learning, including bird detection with reported responses within 15 seconds.
Why it matters
Wildlife detection is a defined operational application whose alert precision and response can be measured.
What remains unproven
Independent detection and false-positive performance has not been provided.
Terminal 3's face-recognition check-in and boarding are separate passenger-processing services. Published checkpoint improvements cannot simply be assigned to the digital twin or wildlife AI.
Full-journey face recognition at Lanzhou Zhongchuan Terminal 3 · Deployed
Passengers at Lanzhou Zhongchuan's Terminal 3, which opened on 20 March 2025, can use their face from check-in through security to boarding. CAAC News reported in March 2025 that the terminal has 63 security lanes and 85 self-boarding units.
By September 2025 the average security check took under three minutes, about 40% faster than conventional lanes, CAAC News reported on 21 September.
A year after opening, China Gansu Net said AI and face recognition run across check-in, security and boarding, with 26 self-service verification gates and verification in under five seconds.
A control room is valuable for the actions it enables
Lanzhou's central operating picture is an important infrastructure case, with specific AI applications alongside it.
The next useful evidence would trace each alert or forecast to an identifiable decision and verified result.
Live data from the Aerostack register. Status reflects published evidence only. See Our approach for how records are graded.
Aerostack register · 3 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.
