In this report, a method for monitoring activity at a ticket machine is presented. While this work has been done in the specific context of Turin metro, the proposed model could be applied to other locations and tasks in video-surveillance. Monitoring the activity is based here on event recognition, by modelling directly the events of interest.We especially focus on detecting queues at ticket vending machines. A 2-layer model is proposed. In the first layer, several sub-events are defined and detected using a discriminative approach (SVMs). The second layer uses the result of the first and model the high-level event of interest. Results are assessed on 4 hours of real video footage coming from Turin metro station.