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Volume: 30 | Article ID: art00020
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Fast, Automated Indoor Light Detection, Classification, and Measurement
  DOI :  10.2352/ISSN.2470-1173.2018.15.COIMG-271  Published OnlineJanuary 2018
Abstract

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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Craig Hiller, Avideh Zakhor, "Fast, Automated Indoor Light Detection, Classification, and Measurementin Proc. IS&T Int’l. Symp. on Electronic Imaging: Computational Imaging XVI,  2018,  pp 271-1 - 2714,  https://doi.org/10.2352/ISSN.2470-1173.2018.15.COIMG-271

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Copyright © Society for Imaging Science and Technology 2018
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