GridInSight

Abstract

We demonstrate GridInSight, a suite of techniques that leverage low-cost, non-intrusive, and commodity smartphone and machine vision cameras to measure electricity grids. Specifically, we develop techniques to measure electricity grid frequency, phase (indoors), and phase (outdoors) across a mix of cameras with errors of 1-2%, 2-5%, and 3-10%, respectively. Further, we develop a novel technique and show an error of 8-15% for measuring voltage on a lightbulb that our system had not seen previously. The ability to cheaply and pervasively measure power quality with non-intrusive, off-the-shelf hardware can enable a wide range of applications for monitoring electricity grids, particularly in emerging economies.