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Airport intelligence / Jeju International

Jeju puts automated target recognition into security screening

Jeju's CT checkpoint uses automated target recognition, according to industry and supplier reporting. This is a specific AI-assisted task within aviation security.

Jeju International Airport, 2024
Jeju International Airport, 2024. Photograph: Kimhs5400 / CC BY 4.0 (cropped to fit). Shows the airport, not an AI implementation.
The picture at Jeju International

What is happening on the ground

Security screening must identify prohibited items consistently across a high volume of cabin baggage. A missed threat is not an ordinary classification error.

ACI Asia-Pacific and Smiths Detection describe Jeju's HI-SCAN 6040 CTiX checkpoint and AI-assisted object identification. Automated image analysis offers screeners a second interpretation of cabin baggage, but a credible safety assessment must distinguish the items found, the prohibited items missed and the unnecessary alarms staff must resolve.

CT imaging and the automated recognition algorithm are related but should be evaluated separately.

Selected implementations

The application under review

01 / Deployed

Jeju puts automated target recognition into security screening

The operational problem

Screeners require reliable image interpretation and a manageable number of false alerts.

What the sources report

The airport's system is described as Smiths HI-SCAN CT equipment with AI-based automated target recognition.

Why it matters

An installed algorithm can be evaluated against human review and regulated detection requirements.

What remains unproven

No independent detection accuracy, false-positive rate or measured passenger wait improvement is provided.

Sources and verification (2)

Smiths Detection case study · Evidence grade B

ACI Asia-Pacific · Evidence grade B

Evidence supports a reported claim; it does not automatically establish a measured operating benefit.

The wider register

What else is happening at Jeju International?

Related airport systems stay in the wider evidence register. Their maturity and AI involvement should be checked separately from the feature above.

No additional publicly listed deployment records.

Editorial judgement

Jeju's useful next story is the validation of the algorithm, not simply the scanner's availability.

Source attribution and status limits remain attached to the implementation record.

Live data from the Aerostack register. Status reflects published evidence only. See Our approach for how records are graded.

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.