Longitudinal Energy Waste Detection with Visualization
Links to Fileshttps://dl.acm.org/citation.cfm?id=3137162
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Type of Work4 PAGES
conference papers and proceedings preprints
Citation of Original PublicationDavid Lachut , Nilavra Pathak , Nilanjan Banerjee , Nirmalya Roy , Ryan Robucci. 2017. "Longitudinal Energy Waste Detection with Visualization". In Proceedings of ACM Buildsys conference, Delft, The Netherlands, November 2017 (BuildSys ’17), 5 pages.
RightsThis item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.
SubjectsComputer systems organization
Mobile Pervasive & Sensor Computing Lab
Leaky windows and doors, open refrigerators, unattended appliances, left-on lights, and other sources subtly leak energy accounting for a large portion of waste. Formal energy audits are expensive and time consuming and do not capture many sources of leakage and waste. In this short paper, we present a hybrid IR/RGB imaging system for an end-user to deploy to perform longitudinal detection of energy waste. The system uses a low resolution, 16×4 IR camera and a low cost digital camera mounted on a steerable platform to automatically scan a room, periodically taking low resolution IR and RGB images. The system uses image stitching to create an IR/RGB hybrid panoramic image and segmentation to determine temperature extrema in the scanned room. Finally, this data is combined with thermostat set-point information to highlight hot-spots or cold-spots which likely indicate energy leakage or wastage. The system obviates the need for expensive, time-consuming waste detection methods, for professional setup, and for more intrusive instrumentation of the home.