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A Cause Of Data Perturbations In Building Sensors

The Critter temperature sensor device has been developed to understand the full nature of pervasive sensor networks. Off the shelf integrated sensor devices incorporate some amount of adaptation to make the devices more reliable. For instance, they use a weighted averaging scheme to account for large fluxuations in temperature, primarily considered to be sensor failures. A weighted average is used to limit the effects of data outliers, considered to be sensor failures. The Critter provides raw instantaneous readings including outlier data that may be considered anomalies or perturbations. We have deployed Critter data sensors pervasively through one academic building for almost 18 months. This paper explores the causes of temperature data perturbations, two temperature data readings taken within seconds of each other that differ by several degrees. Temperature sensor data perturbations are actually the effects of user activity within buildings. By capturing the raw data without automatic processing, we are able to show a correlation between time of the work day, and the frequency of data perturbation.