Recognizing hand gestures using solar cells
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 signatur...
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| Main Authors: | , , , , , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2023
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/7014 https://ink.library.smu.edu.sg/context/sis_research/article/8017/viewcontent/Recognizing_Hand_Gestures_using_Solar_Cells.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
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