Incheon Int'l Airport uses AI to predict baggage system failures

Incheon International Airport, South Korea's primary international hub, has implemented artificial intelligence (AI) technology to proactively detect potential issues within its baggage handling system (BHS) prior to any equipment breakdowns, according to the airport's operator. The BHS Smart Monitoring System was officially launched on October 26 at Terminal 2, which houses a vast network of conveyor belts and sorting machines that transport checked baggage between check-in counters, aircraft, and arrival terminals.

The system continuously monitors critical components, such as baggage sorters, conveyor drive motors, and arrival hall carousels, by capturing real-time data through sensors. Machine-learning algorithms then process this information to identify parts with a high likelihood of failure. The results are visually represented on a three-color gradient scale, ranging from green (indicating normal operation) to red (signaling imminent danger), along with the probable cause behind each potential issue.

This allows maintenance personnel to address problems proactively, either by replacing faulty parts or implementing other preventive measures, thus avoiding potential breakdowns. The traditional method primarily involved reactive repairs, which only occurred after a fault had been identified.