A new airport solution uses artificial intelligence (AI) to reduce waiting times and flight delays caused by congestion at check-in, security, retail and aircraft boarding areas.
Developed by Hitachi Vantara, the technology combines computer vision with video analytics and machine learning to help airline and airport staff identify when and where congestion and delays are occurring and take action to address them – even during the busiest travel times.
The Lumada Video Insights solution uses lidar (light detection and ranging) – a laser-based radar-like technology – to produce a 3D visual model of the airport and the movement of travellers, equipment and luggage in real time.
Video analytics tools are then used to analyse the movement of travellers and luggage throughout the airport, while maintaining passenger privacy and without capturing any personally identifiable information.
As the Hitachi subsidiary explained, comparing the actual movement of travellers to ideal models can help airline and airport staff to identify issues and take action to streamline passengers’ travel experiences from the moment they check in to the moment they (and their luggage) are on board.
The solution is already being piloted by a major US airline, and Hitachi Vantara hopes to implement the technology at more US airports over the next 12 months.
“As someone who travels frequently, I can personally relate to the frustration of airport congestion, long security lines, flight delays and lost luggage,” commented Rich Karpinski, research director for the Internet of Things at 451 Research.
“A new approach has been needed for a long time but the criticality of maintaining personal privacy in public spaces has continued to present a challenge.
“Airports and airlines can now address these issues with the application of lidar, which captures only critical contextual data without the same level of identifying clarity as video, advanced analytics and other video intelligence technologies.”