Data Science in Sensing Machine Generated Data

The increasing recent advances in hardware technology for mobile technology and sensor processing has resulted in greater availability of sensor generated data. For example, mobile devices contain many sensors such as GPS, accelerometers, gyroscope, magnetometer, thermometer, etc., which produce large volumes of data over time. This has lead to a need for principled methods for efficient sensor generated data processing. In this paper, we describe the application of data mining techniques in a case study of identifying patterns to m-health sensor generated data. These technique will be used to build a model for outlier analysis, pattern analysis, and prediction analysis.