CP 420 UofT Transportation Mode Unconstrained Smartphones Sensors Programming Task

Dataset: Transportation Mode Detection with Unconstrained Smartphones Sensors In this final project, we will work on a transportation mode detection data set that was downloaded from the following link:https://arxiv.org/pdf/1810.05596.pdf Identify user’s transportation modes through observations of the user, or observation of the environment, is a growing topic of research, with many applications in the field of Internet of Things (IoT). Transportation mode detection can provide context information useful to offer appropriate services based on user’s needs and possibilities of interaction. Sensors included in the first set (parameter 1) are accelerometer, sound, and gyroscope. These three sensors have the highest values of accuracy taken individually. First dataset Dfirst is formed by twelve features, four for each sensor. Second dataset Dsecond is formed by eight sensor and thirty-two features. Third dataset Dthird formed by all nine relevant sensors and thirty-six features, differ from previous Dsecond only for speed derived features.

Use R coding.