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We design a system, SolarGest, which can recognize hand gestures near asolar-powered device by analyzing the patterns of the photocurrent. SolarGestis based on the observation that each gesture interferes with incident lightrays on the solar panel in a unique way, leaving its distinguishable signaturein harvested photocurrent. Using solar energy harvesting laws, we develop amodel to optimize design and usage of SolarGest. To further improve therobustness of SolarGest under non-deterministic operating conditions, wecombine dynamic time warping with Z-score transformation in a signal processingpipeline to pre-process each gesture waveform before it is analyzed forclassification. We evaluate SolarGest with both conventional opaque solar cellsas well as emerging see-through transparent cells. Our experiments with 6,960gesture samples for 6 different gestures reveal that even with transparentcells, SolarGest can detect 96% of the gestures while consuming 44% less powercompared to light sensor based systems.

SolarGest: Ubiquitous and Battery-free Gesture Recognition using Solar Cells