MechanoBeat
Autor: | Julian Killingback, Huaishu Peng, Tauhidur Rahman, Md. Farhan Tasnim Oshim, Dave Follette |
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Rok vydání: | 2020 |
Předmět: |
Signal processing
Computer science Property (programming) business.industry Deep learning 010401 analytical chemistry 020207 software engineering 02 engineering and technology 01 natural sciences 0104 chemical sciences law.invention Non-line-of-sight propagation law visual_art Scalability Electronic component 0202 electrical engineering electronic engineering information engineering Electronic engineering visual_art.visual_art_medium Leverage (statistics) Artificial intelligence Radar business |
Zdroj: | UIST |
DOI: | 10.1145/3379337.3415902 |
Popis: | In this paper we present MechanoBeat, a 3D printed mechanical tag that oscillates at a unique frequency upon user interaction. With the help of an ultra-wideband (UWB) radar array, MechanoBeat can unobtrusively monitor interactions with both stationary and mobile objects. MechanoBeat consists of small, scalable, and easy-to-install tags that do not require any batteries, silicon chips, or electronic components. Tags can be produced using commodity desktop 3D printers with cheap materials. We develop an efficient signal processing and deep learning method to locate and identify tags using only the signals reflected from the tag vibrations. MechanoBeat is capable of detecting simultaneous interactions with high accuracy, even in noisy environments. We leverage UWB radar signals' high penetration property to sense interactions behind walls in a non-line-of-sight (NLOS) scenario. A number of applications using MechanoBeat have been explored and the results have been presented in the paper. |
Databáze: | OpenAIRE |
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