Brt station door fare evasion control through image recognition using iot approaches

Abstract

Recently some cities have been adopting bus rapid transit systems to decrease public travel times at a relative low cost. The system operation is based on an off-board fare subsystem that collects financial resources from transit passenger. Yet, BRT systems face a fare evasion problem, where users gain access by evading fare controls. Fare evasion through doors not only is a risky practice for the passenger, but also affects bus time scheduling for arrivals to be programmed in an effective way. This paper proposes a control system using image recognition with an IoT and Cloud computing approach for detecting possible bus fares evasions in real time. The application provides a new alternative to detect and report when and where the infraction is committed. The information gathered from the proposed application can be used in the future for analytic analysis allowing to predict possible attempts of bus fares evasions.