Researchers at Georgia Tech developed tiny, battery-free metal tags that emit a brief ultrasonic pulse when touched. The tags are thin metal disks with a hole and cutouts; a tab on a moving part, like a door or drawer, strikes the disk and creates a short pulse people cannot hear but a nearby wearable can detect and log. Yibo Fu, a robotics PhD student who led the work, says the different disk shapes set resonant frequencies so each tag produces a unique "fingerprint" for activity recognition.
Potential uses include counting repetitions at the gym, monitoring faucets or toilet lids to track water use or to signal that an elderly person may need help, and button-style tags to start a timer or record an action. Fu shared the tags in a viral Instagram video that attracted many viewers and comments.
Bolei Deng led the vibration modeling and simulation. The team generated nearly 1,300 initial designs above 20 kilohertz and tested 15 of them. The researchers say the set could grow to dozens, hundreds or even thousands of distinct tags. They used a simple hardcoded algorithm instead of complex machine learning, which lowers computing and power needs. The work was published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.
Difficult words
- ultrasonic — sound waves with frequency above human hearing
- resonant — vibration at a natural preferred frequency
- wearable — small device people can wear on body
- detect — notice or find something with a device
- algorithm — set of rules for solving a task
- simulation — a computer model that imitates real events
- battery-free — working without a battery or external power
- viral — widely shared and seen by many people
Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.
Discussion questions
- Which potential use of these tags would you find most useful in daily life, and why?
- Do you think battery-free wearable devices are safer or more practical for older people? Explain your reasons.
- The researchers used a simple hardcoded algorithm instead of complex machine learning. What are the advantages or disadvantages of that choice for small devices?
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