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Open Access Fast, Automated Indoor Light Detection, Classification, and Measurement

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Lighting is one of the largest power consumers in the United States and around the globe. To better understand how much energy lighting uses in a building, a lighting audit can be performed. Typically, this is a long and manual process, current solutions require significant effort on the part of the auditor. This paper develops a system using commercially available hardware and custom algorithms that enable a single human operator to quickly cover a large area while estimating light positions, type, and surface area. These tasks are accomplished with an error rate of 6.9% and 13.9%, respectively, with surface area estimation within about a factor of two.
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Document Type: Research Article

Publication date: January 1, 2018

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