The technology works on the basis of microphones called Sound Receiving Units, which record acoustic waves transmitted from the surface of objects. They provide the ability to enter data from different surfaces.
The system can work in noisy environments and on objects of different shapes and properties, such as toys, hands, clothing or furniture.
Tapping, swiping and other movements create acoustic waves on the surface of materials picked up by the microphones. The system then uses machine learning to classify these waves and convert them into a solid set of inputs.
SAWSense uses a sealed sensor chamber that completely isolates them from outside noise.
Studies have shown that the system they developed can recognize various types of input, such as hitting, scratching, and movements on the surface of different materials, with an accuracy of 97%.
Source: Ferra
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