Self Calibrated Wireless Distributed Environmental Sensory Networks

Recent advances in sensory and communication technologies have made Wireless Distributed Environmental Sensory Networks (WDESN) technically and economically feasible. WDESNs present an unprecedented tool for studying many environmental processes in a new way. However, the WDESNs' calibration process is a major obstacle in them becoming the common practice. Here, we present a new, robust and efficient method for aggregating measurements acquired by an uncalibrated WDESN, and producing accurate estimates of the observed environmental variable's true levels rendering the network as self-calibrated. The suggested method presents novelty both in group-decision-making and in environmental sensing as it offers a most valuable tool for distributed environmental monitoring data aggregation. Applying the method on an extensive real-life air-pollution dataset showed markedly more accurate results than the common practice and the state-of-the-art.