Publication Type

Journal Article

Version

acceptedVersion

Publication Date

7-2023

Abstract

We design a system, SolarGest, which can recognize hand gestures near a solar-powered device by analyzing the patterns of the photocurrent. SolarGest is based on the observation that each gesture interferes with incident light rays on the solar panel in a unique way, leaving its discernible signature in harvested photocurrent. Using solar energy harvesting laws, we develop a model to optimize design and usage of SolarGest. To further improve the robustness of SolarGest under non-deterministic operating conditions, we combine dynamic time warping with Z-score transformation in a signal processing pipeline to pre-process each gesture waveform before it is analyzed for classification. We evaluate SolarGest with both conventional opaque solar cells as well as emerging see-through transparent cells. Our experiments demonstrate that SolarGest achieves 99% for six gestures with a single cell and 95%for fifteen gesture with a22solar cell array. The power measurement study suggests that SolarGest consume 44% less power compared to light sensor based systems.

Keywords

Photovoltaic Cells, Photoconductivity, Gesture Recognition, Solar Panels, Energy Harvesting, Three Dimensional Displays, Standards, Solar Energy Harvesting, Visible Light Sensing, Gesture Recognition

Discipline

Artificial Intelligence and Robotics

Research Areas

Intelligent Systems and Optimization

Publication

IEEE Transactions on Mobile Computing

Volume

22

Issue

7

First Page

4223

Last Page

4235

ISSN

1536-1233

Identifier

10.1109/TMC.2022.3148143

Publisher

Institute of Electrical and Electronics Engineers

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