IATA Resolution 753, which comes into effect this June, commits airlines to keeping track of baggage movements and aims to significantly reduce mishandled and misdirected bags. But it also creates new volumes of data, which SITA reports, could be handled more efficiently with AI tools like machine learning, robotics and predictive analytics.

In a new report, Intelligent Tracking: A Baggage Management Revolution, SITA shares a vision of interconnected smart devices and applications that can inform each other of baggage movements with limited human intervention.

By embracing new technologies and refining processes, the air transport industry has reduced its baggage mishandling cost from $4.22 billion to $2.1 billion over the past decade.

The objective of Resolution 753 is to reduce that figure further, keeping passengers happy and protecting airlines from liability.

It all starts with RFID (Radio Frequency Identification) tagging. These tags are generally accepted as the most reliable way to keep a unique identifier on each piece of luggage transported, both because RFID tags are relatively easy and affordable to implement and because they able to put up with the inevitable wear and tear of transport.

Hong Kong International Airport (HKIA) became the first international airport to adopt RFID technology in its baggage handling system in 2008. It was also the first airport to build RFID readers into its robotic baggage handling systems—Stack@Ease—that help airport workers load bags into Unit Load Devices (ULDs), effectively automating departure baggage reconciliation.

In the SITA report, Chris Au Young, general  anager, Smart Airport, Airport Authority Hong Kong, credits RFIDs with significantly improving tracking accuracy at the airport and explains how AI is helping to make the process of tracking more efficient.

“Our baggage tag (barcode with integrated RFID chip) has enjoyed a successful read rate of close to 99%. Before the implementation of RFID, the read rate of a traditional barcode-only baggage tag was only about 80%. This is a significant difference given the fact that HKIA handled about 80,000 departure bags every day, and close to 110,000 departure bags per day during peak seasons.”

“Today, we use RFID technology comprehensively in baggage handling, from departure, to transfer and to arrival. It enhances operational efficiency and security, providing better passenger experience. Passengers with MyTAG (an RFID luggage tag) arriving at HKIA will now be notified on smartphones when their luggage is delivered at the baggage reclaim belt. Hence, instead of crowding at the reclaim belt hoping to get their bag firsthand, passengers can make better use of their time while waiting for the baggage.”

“In response to requests from airlines to provide Baggage Processing Messages (BPMs) for both arrival and departure bags, we have added additional RFID readers throughout our baggage handling system to increase track points. We have implemented a platform for the distribution of BPMs to airlines for arrival baggage reconciliation and an arrival bag scanning service will be launched in Q3 2018.

“One of the challenges is for airlines is to provide terminating BSMs (Baggage Source Messages) and BMMs (Baggage Manifest Messages) to facilitate the arrival baggage reconciliation process and as an airport operator, we will do our best to support.

“We also developed a trolley management system that uses machine learning techniques, image-based technologies and existing surveillance CCTV cameras to monitor baggage trolley availability. With over 12,000 trolleys moving around the terminals and transportation center and over 100 trolley pick up points, timely recirculating to ensure these pickup points are always filled is a challenging task. The Real-time Trolley Supply Monitoring System has achieved 92% accuracy, greatly reducing the need for manual checking of trolleys, and the service level of trolley availability for passengers in the baggage reclaim hall has been improved.

“With artificial intelligence (AI), end-to-end bag tracking can be even more complete. AI-powered video analytics will be able to track the transport of baggage containers from plane-side to the baggage processing hall, providing passengers with better estimation on the baggage delivery status. We see there are opportunities to use AI in further optimizing the tracking of baggage and become part of the future standard in airport operations.”