Battery-free RFID sensing system offers real-time, reliable data

What if the identical RFID “sensible barcode” tags used to trace packages and retail stock may additionally detect modifications in the actual world—like temperature, stress or weight—with out batteries or added {hardware}?

That concept’s now a actuality, due to a staff of researchers out of UC San Diego’s Heart for Wi-fi Communications (CWC) and Qualcomm Institute who’ve developed a strong and real-time RFID-based passive sensing system, i.e. a way that may measure naturally occurring phenomena utilizing harvested radio frequency (RF) vitality.

Ishan Bansal, a second-year grasp’s scholar in pc engineering, and Dinesh Bharadia, an affiliate professor {of electrical} and pc engineering on the Jacobs College of Engineering, are spearheading the cost with a brand new paper.

Named SenSync, the software-based innovation just lately earned the Greatest Paper Award on the 2025 IEEE RFID Conference. The paper is titled “SenSync: Real-Time and Accurate Passive Sensing.”

“In contrast to lots of conferences, IEEE RFID has lots of business involvement,” defined Nagarjun Bhat, a co-author of the award-winning paper, “SenSync: Actual-time and Correct Passive Sensing,” and a Ph.D. scholar in electrical engineering on the Jacobs College of Engineering.

“It is a house the place there’s lots of commercializable potential, as a result of firms take the concepts from right here and use them to construct a product that may attain hundreds of individuals sooner or later.”

Lead writer Bansal defined that SenSync is a significant leap ahead for passive sensing, because it highlights how present RFID infrastructure could be retooled to allow real-time, battery-free sensing. Low-cost RFID tags are already utilized in billions of merchandise globally.

Whereas earlier work from Bhat and CWC laid out how RFID tags can be utilized to sense knowledge from a {hardware} standpoint, SenSync is what brings the picture into focus.

When utilizing a differential sensing system that includes two RFID ICs related to the identical antenna, it is doable for them to intrude with one another. As a substitute of sending their knowledge to the reader concurrently, Bansal famous the information would arrive sequentially. That may trigger slight variations within the knowledge streams, which makes it troublesome to find out the proper values.

“My algorithm places the 2 divergent sequences collectively and is smart out of it,” stated Bansal. “This permits us to sense clearly, repurposing RFID to get dependable sensor knowledge with out wires or batteries.”

Fixing long-standing challenges in passive RFID sensing

RFID methods have historically been optimized for identification, not sensing—they’re what’s used to trace packages or checked baggage. Whereas different comparable methods like Bluetooth exist, RFID units are rather more mature and widespread. About 50 billion RFID tags are offered yearly, Bansal stated, in comparison with 4 to 5 billion Bluetooth units.

However regardless of their availability, implementing RFID methods is not all the time straightforward.

Business RFID readers are required to observe strict communications protocols that always embrace frequency hopping or sequential tag studying; in follow, which means presumably distorted alerts and timing mismatches have traditionally made sensing purposes notoriously unreliable.

SenSync solves these issues utilizing an algorithm known as dynamic time warping (DTW), which was initially utilized in speech recognition.

So, how does it work? SenSync synchronizes—therefore the title—knowledge streams from a number of passive RFID tags and makes use of differential sign behaviors to get dependable readings.

“We do not wish to change the fundamental knowledge,” Bansal defined, “We simply wish to match it nicely.”

He famous that SenSync delivers 5 instances larger sensory decision and eight instances the information throughput in comparison with earlier passive RFID sensing strategies, that means it will probably course of as much as 500 knowledge samples per second with sub-degree error charges, even in complicated, dynamic environments.

“We had been capable of present that the information stream may very well be pushed each second with out shedding any accuracy or constancy,” he added.

Actual-world sensing, reimagined

That improved sensing functionality opens up sensible purposes starting from automating warehouses and monitoring agricultural plots to enhancing medical sensing and measuring meals waste.

Already, Bansal, Bhat and the remainder of their analysis staff have highlighted how SenSync can work in an augmented actuality (AR) setting and had been additionally acknowledged on the SenSys 2025 convention (co-hosted by ACM and IEEE) for having the Greatest Demo—Runner-up.

Utilizing a smartphone-based AR app, convention attendees at IEEE RFID 2025 noticed in actual time how RFID tags may present the quantity of power utilized or visualize the moisture content material in a pot of soil by means of AR.

Or, Bhat stated, think about a warehouse stuffed with bins upon bins. You possibly can simply level your telephone digital camera or AR glasses at a field and immediately see its weight with out ever touching it, he defined.

“AR at present is generally restricted to what your imaginative and prescient feed supplies you,” he famous. “However, the multimodal sensing enriches the information by pulling within the stimuli like temperature that we will not see. That is all carried out by the algorithm; with out that, all the information you’d accumulate can be noisy and troublesome to course of in actual time.”

And, as a result of SenSync is battery-free, runs on industrial RFID tags and requires no coaching knowledge or recalibration, Bansal stated that it provides a extra sustainable, scalable sensing resolution that may function reliably in indoor, outside, or cellular environments.

“Our resolution is definitely really ubiquitous,” he stated, explaining that “you may drop it anyplace, and it will work the identical approach.”

From RFID to bodily AI

Bhat, Bansal and Bharadia really feel that SenSync may very well be extra than simply an improve to passive sensing—it may very well be the muse of bodily AI that hyperlinks the actual and digital worlds.

“Massive language fashions (LLMs) are powering AI round us,” Bharadia defined, including that the majority machine studying attracts on textual content, voice or pictures, all of that are extensively accessible and simply accessible. However different sensory data like temperature and humidity aren’t but accessible for somebody to construct an LLM. “To empower our bodily areas with AI, you would want sensors and sensing.”

“SenSync is really an innovation,” he added, “that may present that battery-free sensing and achieve this with extraordinarily low energy utilization and no wires.”