Road crossing recognition through smartphone´s accelerometer

Sensor-enabled smartphone´s are becoming a mainstream platform for researchers to collect data which could prove useful for discovering patterns in human behavior. Yet, employing sensorial data to extrapolate information is not clear and deserves investigation. In this article, we discuss movement pattern recognition in day-by-day urban street behavior. As a case study, we aim at recognizing when a pedestrian stops crosses a street ruled by a traffic light; to do so we only use data coming from the accelerometer of the pedestrian´s smartphone.