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Researchers turn low-cost RFID tags into scalable passive sensors

Researchers turn low-cost RFID tags into scalable passive sensors

Technology News |
By Jean-Pierre Joosting



The rapidly growing IoT has made data more readily available and easily accessible than ever. Sensors, “smart” devices and software connect our world to the cloud, gathering information and enabling new types of data sharing and analysis. However, most of these tools are battery-powered and have difficulty sensing changes in real time. 

To address these shortcomings researchers at UC San Diego have used low-cost RFID tags to develop analog passive sensors that do not require batteries and can be easily scaled. The development has enabled real-time analog sensing with commercially available RFID tags, antennas and readers.

According to Dinesh Bharadia, an associate professor at UC San Diego in the Department of Electrical and Computer Engineering with an affiliate appointment in the Department of Computer Science and Engineering and the Qualcomm Institute (QI), “data will be the next decade’s ‘silicon.’” 

New research published in the Proceedings of the ACM Conference on Embedded Networked Sensor Systems from Bharadia and lead author Nagarjun Bhat demonstrates that not only is passive sensing — or sensing without being connected to a power source — possible, it can be done at little cost without any specialized equipment. 

A Ph.D. student in electrical engineering, Bhat’s research focuses on ways to enable passive sensing using simple, widespread commodities, in this case RFID tags. 

RFID tags run between a few cents to a few dollars per chip depending on the specifications. Further, with up to 90% of retailers using RFID technology, the chips are widespread and easy to access. They are commonly embedded in products like clothing or library books for tracking inventory or in contactless transit fare payment cards. 

“We wondered whether we could repurpose RFID tags to do battery-free sensing and tracking,” said Bhat. He explained that most current approaches to passive sensing rely on analog-digital converters, which measure stimuli, record them in raw data and convert them to digital values that are readable by computers. However, these types of sensor interfaces are power-hungry and without additional batteries, they can last a matter of hours. Battery-based systems are also bulky, expensive and hard to scale sustainably.

“We were trying to see if we could use the chips to directly sense stimuli without needing converters,” he added. “We wanted to know if our environment could be automated in a way that was battery-free, able to sense parameters like temperature and humidity, and could connect to the IoT to send raw data to a reader that could make sense of it all.”

 

Real-time data through RFID tags

In an attempt to make passive, wireless interfaces, other researchers have pursued ultra low-power digital sensing that couples a sensor, converter and microprocessor into a single package. While an efficient design, these types of devices are expensive, bulky, and lack the ability to sense and report stimuli in real time. They only send data to a reader when it’s requested and need complex electronic circuitry for their interface.

“If I wanted to use digital sensing for a biomedical application like monitoring a patient’s heart rate, I might not be able to access that data for 10 minutes,” Bhat said. “That’s a problem.” 

Analog sensing — the category in which Bhat and Bharadia’s sensors fall — directly perceives environmental stimuli. Unlike digital interfaces, analog ones convert the change in voltage/current produced by sensors into parameters of a wireless signal.

Bhat noted that although “there has been good work done so far” on passive analog systems, most of the research has relied on customized sensors that are purpose-built and only suited for a particular application. These systems are difficult to generalize, he explained, adding that “you’d have to redesign all sensors on the market to make them commercially available.”
This why the researchers chose RFID tags as the workhorse for their passive sensors — they’re commercialized, cheap and require little custom hardware to be deployed or read. 

“We took the concept of analog sensing and made it real-time,” Bhat said. “You don’t need any fancy interfaces, specialized readers or batteries to access the data — all you need are some commercially available RFID tags, antennas and readers.”

 

The future of data collection

Bhat’s battery-free RFID sensors enable new use cases like improved agricultural management, real-time athletic performance metrics and occupancy detection. 

For example, currently automatic irrigation systems generally rely on a smaller quantity of bigger sensors that cover large areas. This can be cost-effective, although it comes at the expense of data specificity. RFID-based passive trackers can do both. By deploying soil moisture sensors at scale around a field, it’s possible to use a few RFID readers to remotely measure moisture content at a much more granular level and adjust how water is distributed based on current conditions. 

This type of immediate data can also be valuable for athletes. For instance, many UC San Diego athletes engage in force plate testing as part of their training, where they jump on force plates that measure their strength, power and posture. These tests must be done at a special facility and can be expensive. Bhat’s paper describes how RFID sensor tags could be used to bring these tests “in-house” by embedding them in shoe soles to measure an athlete’s jumping force.

Or, RFID tags can be placed in parking garages to measure occupancy and map where and how many spaces are being used. A chip could be added to the floor of every space; when a car pulls into the spot and covers the light-sensitive sensor, the tag recognizes that the spot is occupied and can send that information to a central location. 

However, Bharadia and Bhat see bigger uses for their work. 

“AI is everywhere now,” Bharadia said, adding that AI is powered by data enabled by sensors. “We’re at the cusp of a revolution where new sensors will be collecting the data that will power the next generation of AI. Using batteryless sensors lets us collect a lot of information that’s otherwise challenging to access — they can empower data collection, and this innovation marks a really important direction for the future.”

Bhat and Bharadia presented their research on at the 22nd ACM Conference on Embedded Networked Sensor Systems (SenSys 2024) in Hangzhou, China.

https://doi.org/10.1145/3666025.3699342

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