Sensor-based approach for predicting departure time of smartphone users

Ron Biton, Gilad Katz, Asaf Shabtai

2015 2nd ACM International Conference on Mobile Software Engineering and …, 2015

While location prediction of smartphone users has made great strides in recent years, a major challenge remains. As users spend the majority of their time is several fixed locations (home, work), existing algorithms are unable to identify the exact time in which a person is likely to depart from one place to another. In this work we present a sensor-based approach designed to predict the departure time of users. By using location and accelerometer sensors we were able to train a generic classification model that is able to predict whether the user will stay put or move to a different location with true positive rate of 0.73 and false positive rate of 0.3.