AWAAIT’s fare dodging detection system DETECTOR wins Phase 1 grant of the European H2020-SME Instrument

The Barcelona-based start-up has signed a Grant Agreement, valued in €50k, with the European Commission to develop a Feasibility Study.

Barcelona, December 2014 – AWAAIT, through its R&D business unit HAL, has won a Phase 1 grant of the H2020-SME Instrument program. The European Commission has conceded the start-up a €50k fund to develop a feasibility study within the following five months for its TRAINSFARE project, aimed to tackle fair evasion in public transport via the Artificial Intelligence-Machine Learning system DETECTOR.

DETECTOR is an automatic real-time video analytics system that detects fare evasion on public transport. Via Artificial Intelligence-Machine Learning algorithms, a camera over the ticket barrier observes the ticket validation process. The system immediately sends a sequence of images to inspectors’ smartphones when detecting a fare dodging incident. This allows to intercept offenders before they reach the platform.

DETECTOR has been developed in collaboration with the regional and commuter train operator Ferrocarrils de la Generalitat de Catalunya (FGC) as part of their “Smart Train programme”. The system has been validated after a 3-month test at FGC’s Provença station in Barcelona, where it has proven its effectiveness in reducing fare dodging.

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