Artificial intelligence supervises social distancing in metros

Passengers wait for a train in Panama Metro, source: Metro de Panamá

In order to meet safety requirements in pandemic times, public transport operators need new innovative solutions. To this end, French technology and rolling stock company Alstom has applied its AI-based mobility supervision system to monitor social distancing in metro trains and stations.

Last year Alstom deployed its Mastria supervision solution, which uses artificial intelligence and other technologies, in Panama Metro to analyse passenger flows and avoid overcrowding at some stations during the peak hours. The first results were achieved three months later. They showed that the AI-based system is able to predict saturation of a station up to 30 minutes before it could be visibly observed. As a result, the metro operator has extra time to take some remedial actions.

New purpose

After the coronavirus outbreak had occurred, the Alstom-developed system was adapted for the new purpose, i.e. to keep an eye for social distancing in metro trains and stations. Currently, Metro de Panamá, an operator of the metro system in Panama, is maintaining the train’s load at a level of no more than 40 per cent of its maximum capacity that was prescribed by the country’s health authorities. And the Mastria solution assists the metro operator in implementing this policy. “To predict is to prevent. The ability of this tool to analyse millions of pieces data in real-time makes it an indispensable ally for operators at all times, but especially in the current context,” said Stephane Feray-Beaumont, Vice President Innovation & Smart Mobility at Alstom Digital Mobility.

Mastria solution

The Mastria supervision system is based on four main standard functions: multimodal supervision, traffic management, coordination of operations and predictive analysis. These functions are highly configurable and can be combined according to the needs of operators and the global mobility network environment. The solution uses data from various sources: train weight sensors, ticketing machines, traffic signalling, management systems, surveillance cameras and mobile networks. As a result, it is able to monitor, control and predict passenger density and operations in real-time. Besides Panama, Mastria was also tested in Paris, Florence and Zaragoza.

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Author: Mykola Zasiadko

Mykola Zasiadko was editor of online trade magazines and

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