Computer Vision software trialed to measure passenger flow on regular train routes in Lithuania

Pilot: Computer Vision software trialed to measure passenger flow on regular train routes in Lithuania

Technology company Agmis has introduced a Computer Vision-based software solution for measuring passenger flows in public transport.

In February the company conducted a pilot railways MLOps project on ten local trains using information from existing video surveillance cameras.

The experiment was performed in cooperation with the Mobility Innovation Center, whose stakeholders are AB Lietuvos Geležinkeliai (Lithuanian Railways).

Computer Vision-based software counted passengers entering and exiting the train at each stop, passengers with children, animals as well as passengers transporting bicycles.

By augmenting real-time passenger flow information with ticket sales data, the solution can help to reduce the number of passengers traveling without a ticket.

Computer Vision technology was selected, as AI can identify company employees in the train, filter out accompanying persons who might enter and exit the train at the station, recognize luggage and other bulky items such as bicycles.

“This experiment helps to evaluate the use of AI for optimization of business processes for companies in the public transport sector, as well as to improve the quality of services for the passengers. This technology can be easily introduced in any kind of mass transit system and it will become a standard tool of choice in the near future” – noted Innovation Expert of Mobility Innovation Center Kęstutis Vanagas.

The Computer Vision software for the project was developed by Agmis AI spinoff EasyFlow. EasyFlow provides MLOps solutions and develops Computer Vision solutions for retail, industrial, and aerial diagnostics verticals.

“Computer Vision provides real-world analytics. In our projects, we utilize the technology for power grid infrastructure analysis, measure road surface quality, and perform monitoring of infrastructure sites. As specific models can be trained for a particular task, there are a lot of potential technology applications” – added CEO at EasyFlow Simas Jokubauskas.

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