Environmental Monitoring of Continuous Phenomena by Sensor Data Streams: A System Approach Based on Kriging

Abstract

Environmental monitoring as technological endeavor has to deal with limitations in respect to transmission capacities, computational resources and storage space. Despite the progress in ICT, those limitations remain significant because of rising demands like real-time monitoring on the one hand and increased amount of observations on the other. The geostatistic method of kriging, originally developed to manage spatial uncertainty, provides elaborate means for spatio-temporal interpolation and is therefore the method of choice wherever continuous phenomena are to be monitored by discrete observations. With its associated confidence estimation, the method can also be exploited to solve other problems like fusion of sub-models for continuous real-time updates or filtering massive sensor streams. In this work, we suggest a system, substantially based on kriging, to filter, process, interpolate, monitor and archive sensor data streams. We incorporate several algorithmic and technical solutions into this system and evaluate them by simulated and real data.