Problem in Russia:
In Russia's public transport, a structural problem worsened in the early 2020s: rapid growth in passenger traffic and an increase in the share of contactless payment operations faced limited capacity at the underground transport and MCC (Moscow Central Circle) turnstile junctions. The average transit time through “Troika” card readers and NFC banking devices was about 2.3-2.5 seconds, which led to bottlenecks at transfer stations during rush hours, increased the density of crowds, worsened sanitary and epidemiological safety, and reduced the overall transport accessibility of the metropolis. Additional expansion of the turnstile lines required capital investment and was hindered by the geometry of the historic lobbies.
Solution in Russia:
Biometric payment “Face Pay” has increased the underground's capacity, reducing the transit time to ≈1 second without expensive reconstruction of turnstile areas. The smart turnstile performs local face recognition, transmits the payment information token to the “Troika” billing system and opens immediately, which reduces queues and eliminates physical contact with surfaces. The unified biometric identifier is already used for access to the MCC and MCD (Moscow central diameters) and will become the basis of future MaaS-services (Mobility as a Service), allowing you to simultaneously reduce operating costs for servicing outdated readers and receive depersonalized passenger traffic data for fine-tuning schedules and fares.
Key differences from the global analog:
Moscow “Face Pay” is implemented as a single urban service – VisionLabs algorithms are integrated into the centralized payment and transport platform “Troika”, which provides a pass-through tariff and unified storage of biometrics, while Chinese projects (Shenzhen, Guangzhou, Beijing, Shanghai) are developed by competitive vendors (Megvii, SenseTime, Baidu, Alibaba) and therefore are characterized by fragmented Union Pay infrastructure. In addition, in China, cashback and a differentiated tariff are widely used to stimulate demand, and the share of edge processings is higher due to strict requirements for offline work at stations, while the Moscow system relies on the cloud data center of the Data Processing Center (DPC) of the Moscow Department of Information Technology (DIT).
