SolarGest: Ubiquitous and battery-free gesture recognition using solar cells

• Main Authors: MA, Dong, LAN, Guohao, HASSAN, Mahbub, HU, Wen, UPAMA, B. Mushfika, UDDIN, Ashraf, YOUSEEF, Moustafa
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Artificial Intelligence and Robotics
• Online Access: https://ink.library.smu.edu.sg/sis_research/7010; https://ink.library.smu.edu.sg/context/sis_research/article/8013/viewcontent/3300061.3300129.pdf
• Institution: Singapore Management University

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 distinguishable 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 with 6,960 gesture samples for 6 different gestures reveal that even with transparent cells, SolarGest can detect 96% of the gestures while consuming 44% less power compared to light sensor based systems.