The solution, which uses Big Data and Machine Learning, allows operators to adapt, easily and in real time, their offer to the social distancing and public gathering requirements that have arisen due to the Covid-19 pandemic. Mastria gives operators higher visibility on passenger distribution and flow in trains and stations, as well as enhanced predictive capabilities.
This equates to the ability to anticipate, control and manage passenger density in real time, adapting frequency, capacity and the required number of trains, as well as passenger flows into stations, among other things. This is especially useful for managing fluctuating demand peaks, such as during rush hours, special events, special mobility restrictions, etc.
Alstom’s solution aggregates information on passenger demand and flows from train weight sensors, ticketing machines, traffic signalling and management systems, surveillance cameras and mobile networks in order to offer a real-time picture of passenger flows.
Mastria processes the information and provides operators with recommendations to ensure specified levels of occupation. Thus, it can suggest increasing trains frequency, redistributing the flow of people to particular stations, readjustments to other transport systems, restricting entry to stations or even managing the distribution of passengers on the platform to align them with cars with more space on them.
Mastria’s prediction algorithms anticipate these situations, allowing proper planning of the entire system. The ability to predict and analyse millions of pieces of data in real time makes it possible to anticipate passenger flows and adapt offer to real or expected demand.