Mobile Sensing Data for Urban Mobility Analysis: A Case Study in Preprocessing

Provided by: RWSoftware
Topic: Mobility
Format: PDF
Pervasiveness of mobile phones and the fact that the phones have sensors make them ideal as personal sensors. Smart phones are equipped with a wide range of motion, location and environment sensors that allow the user to analyze, model and predict mobility in urban areas. Raw sensory data is being collected as time-stamped sequences of records, and this data needs to be preprocessed and aggregated before any predictive modeling can be done. This paper presents a case study in preprocessing such data, collected by one person over six months period.

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