An Open Problem: Energy Data Super-Resolution

Rithwik Kukunuri, Nipun Batra, Hongning Wang
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引用次数: 2

Abstract

In this notes paper, we present an open problem to the Buildsys community: energy data super-resolution, referring to the task of estimating the power consumption of a home at a higher resolution given the low-resolution power consumption. Super-resolution is especially useful when the smart meters collect data at a very low-sampling rate owing to a plethora of issues such as bandwidth, pricing, old hardware, among others. The problem is motivated by the success of image super resolution in the computer vision community. In this paper, we formally introduce the problem and present baseline methods and the algorithms we used to "solve" this problem. We evaluate the performance of the algorithms on a real-world dataset and discuss the results. We also discuss what makes this problem hard and why a trivial baseline is hard to beat.
一个开放的问题:能源数据超分辨率
在这篇论文中,我们向Buildsys社区提出了一个开放的问题:能源数据超分辨率,指的是在低分辨率功耗的情况下,以更高分辨率估计家庭的电力消耗。由于带宽、价格、旧硬件等诸多问题,当智能电表以非常低的采样率收集数据时,超分辨率尤其有用。这个问题是由图像超分辨率在计算机视觉界的成功所激发的。在本文中,我们正式地介绍了这个问题,并给出了我们用来“解决”这个问题的基线方法和算法。我们在真实数据集上评估了算法的性能并讨论了结果。我们还将讨论是什么使这个问题变得困难,以及为什么一个微不足道的基线很难克服。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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