We describe the design, deployment, and experience with a wireless sensor network for high-fidelity monitoring of electrical usage in buildings. A network of 38 mote-class AC meters, 6 light sensors, and 1 vibration sensor is used to determine and audit the energy envelope of an active laboratory. Classic WSN issues of coverage, aggregation, sampling, and inference are shown to appear in a novel form in this context. The fundamental structuring principle is the underlying load tree, and a variety of techniques are described to disambiguate loads within this structure. Utilizing contextual metadata, this information is recomposed in terms of its spatial, functional, and individual projections. This suggests a path to broad use of WSN technology in energy and environmental domains.<\/p>\n","protected":false},"excerpt":{"rendered":"
We describe the design, deployment, and experience with a wireless sensor network for high-fidelity monitoring of electrical usage in buildings. A network of 38 mote-class AC meters, 6 light sensors, and 1 vibration sensor is used to determine and audit the energy envelope of an active laboratory. 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