Longitudinal energy waste detection with visualization
Longitudinal energy waste detection with visualization
复制标题
可视化纵向能源浪费检测
DOI：
10.1145/3137133.3137162
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Robucci, Ryan
中科院分区：
文献类型：
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作者：
Lachut, David;Pathak, Nilavra;Banerjee, Nilanjan;Roy, Nirmalya;Robucci, Ryan
漏水的门窗、打开的冰箱、无人看管的电器、常开的灯和其他来源都会巧妙地泄漏能源，这些能源占浪费的很大一部分。正式的能源审计既昂贵又耗时，并且无法捕获许多泄漏和浪费的来源。在这篇简短的论文中，我们提出了一种混合 IR/RGB 成像系统，供最终用户部署以执行能源浪费的纵向检测。该系统使用低分辨率 16 x 4 红外摄像机和安装在可操纵平台上的低成本数码相机来自动扫描房间，定期拍摄低分辨率红外和 RGB 图像。该系统使用图像拼接来创建 IR/RGB 混合全景图像，并使用分割来确定扫描房间中的温度极值。最后，该数据与恒温器设定点信息相结合，以突出显示可能表明能量泄漏或浪费的热点或冷点。该系统无需昂贵、耗时的废物检测方法、专业设置以及更具侵入性的家庭仪器。
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 x 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.
低成本连续热传感
DOI：
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发表时间：
2011
期刊：
International Conference on Systems for Energy-Efficient Built Environments
影响因子：
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作者：
V. Rao;Anthony G. Rowe
通讯作者：
Anthony G. Rowe
最大限度地减少家庭能源测量的干扰
DOI：
10.1145/2422531.2422543
发表时间：
2012
期刊：
Proceedings of the Fourth ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings
影响因子：
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作者：
David Lachut;S. Piel;Lazeeb Choudhury;Yucheng Xiong;Sami Rollins;Kevin Moran;Nilanjan Banerjee
通讯作者：
Nilanjan Banerjee
基于声学的设备状态识别，用于细粒度能源分析
DOI：
10.1109/percom.2015.7146510
发表时间：
2015
期刊：
2015 IEEE International Conference on Pervasive Computing and Communications (PerCom
影响因子：
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作者：
Pathak, Nilavra;Khan, Md Abdullah;Roy, Nirmalya
通讯作者：
Roy, Nirmalya