Engineering and computing researchers create simple metal tags with unique ultrasonic fingerprints to detect door openings and other movements.
Friday, 17 April 2026
Blank Space (small)
(text and background only visible when logged in)
Most smart home devices require power one way or another. You have to plug them in, recharge them, or replace their batteries at some point.
Georgia Tech researchers think they have a better way with small metal tags that can signal when a door or drawer is opened, count reps in the gym, or even track bathroom use for elderly relatives. Their tags are battery-free, quiet, inherently private, and cost only a few cents each. They’re smaller than a penny.
Like other kinds of smart home sensors, the tags are designed to be mounted on a cabinet or doorframe, for example, using a 3D-printed base. A small tab is attached to the corresponding door or drawer. When it’s opened, the tab strikes the metal disk, triggering a brief ultrasonic pulse imperceptible to human ears but detectable by a wearable device that logs the activity.
The shape of the metal tag — a small disk with a hole in the center like a flat washer and various cutouts along the outer edge — determines the frequency of the sound, so each tag can be uniquely identified.
“Those unique fingerprints can be used for smart home sensing, or what we call ‘activity recognition,’” said Yibo Fu, a robotics Ph.D. student who led development of the tags with other engineering and computing researchers.
Fu said the tags could be attached to faucets to help monitor water use or toilet lids to alert caregivers that an elderly relative might need assistance in the bathroom. Attached to weights in the gym, they could count squats or presses. Users could manually press button versions to trigger a timer or log an activity.
Fu recently described the tags on Instagram in a viral video that’s generated 1.6 million views and counting, 150,000 likes, and hundreds of comments. Among the reactions are people proposing other uses and asking for a crowdfunding campaign to make them a reality.
“There are some pretty interesting comments from people in other fields,” Fu said. “One mentioned using the tags in archiving systems where you have huge shelves and libraries of boxes. When you remove a box or store a new box, there's a rapid motion, and you would trigger the tags and know exactly what thing you just opened, closed, or archived. Someone else mentioned tracking locations for thousands of garbage and recycling bins in waste management systems.
“Those are more specialized scenarios, but it’s been fun to see those comments and ideas.”
Bolei Deng in the Daniel Guggenheim School of Aerospace Engineering specializes in vibration and waves and how geometry of an object influences its resonance. He and his team created a modeling and simulation tool to design the metal disks so they would generate specific ultrasonic frequencies when they’re struck.
Their simulations identified nearly 1,300 initial designs that would each produce a unique frequency in the ultrasound range. Those frequencies are above 20 kilohertz, which is the upper limit of sounds humans can hear. The team used 15 of the proposed designs in their tests.
“We could select 20 or 50 or 100 designs and it most likely still works,” Deng said. “And with more careful design, I think the total number of available tags can be very, very large — easily thousands — because the ultrasound frequency range is very broad.”
Using ultrasound presents advantages beyond their silence to human ears. They’re easy to pick out even in noisy environments. And they don’t travel very far, so only nearby microphones would “hear” the tag. That makes the devices inherently private, Deng said, because other people wouldn’t detect any activity unless they were within a meter or so.
One other way the researchers worked to keep their system simple: they did not use any complicated machine learning algorithms to detect the ultrasound signatures. Instead, they created an algorithm with simple, hardcoded rules. That approach means identifying signals requires little computational and electrical power.
Along with Deng, Fu worked on the tags with School of Interactive Computing researchers Alexander Adams and Josiah Hester.
“This has really been a collaboration between computing and engineering,” Fu said. “There is the physics simulation part, but also there's the computing we needed to design the algorithm for reading the signals.”
Blank Space (medium)
(text and background only visible when logged in)
About the Research
This research was supported by the National Science Foundation, grant Nos. IIS-2228983 and CNS-2430327; the Alfred P. Sloan Foundation; VMWare; Google; and Catherine M. and James E. Allchin. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of any funding agency.
Citation: Yibo Fu, Vivian Shen, Víctor Riera Naranjo, Bolei Deng, Alex Adams, and Josiah Hester. 2025. SoundOff: Low-cost Passive Ultrasound Tags for Non-invasive and Non-Intrusive Smart Home Sensing. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 9, 4, Article 174 (December 2025), 32 pages. https://doi.org/10.1145/3770666
Preeminence in Research
The College of Engineering conducts more than $312 million in research each year. As a critical part of our educational mission, faculty and student researchers focus on tackling the most challenging issues of our time and improving the human condition.
Read more about Preeminence in Research
Wearing the Future
02 December 2025
From smart textiles to brain-computer links, Georgia Tech engineers are designing wearables that connect humans and machines more closely than ever to sense, respond, and heal.