Measurement Analysis of the Live E! Sensor Network: Spatial-Temporal Correlations and Efficient Data Aggregation
Abstract
The (Japanese) Live E! project consists of a large sensor network of spatially distributed weather stations measuring different environmental quantities such as temperature, humidity, pressure, etc. Our goal is to conduct the first analysis on this huge data set of the structures of correlations both in time and space observed on data, for given quantity amongst stations, and for a given station, amongst sensors. Finally, we investigate a data aggregation algorithm, based on polynomial regression, and we show how it can reduce significatively the overall data traffic.