Standard passive RFID tags work by the reader sending a signal that provides just enough electromagnetic energy to cause the RFID tags to broadcast its data, typically a simple, unique identifier. In the past, the reader simply picked up this code to identify whether the object was present or not-on or off, signal or no signal.
A new approach to RFID from academics at the University of Michigan offers a different approach, the engineers there say. Called IDAct, the researchers say the technology improves on the current approach by providing a more nuanced reading of the signal from the RFID tags.
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This allows the reader to detect minute fluctuations in the signal coming back from tags to detect when an object is moved or whether a person is touching it. It can also detect changes in a room's electromagnetic field to infer, for example, when a human is present.
"Every object causes electromagnetic interference in a specific way. We can use that information, along with information from RFID tags, to get a very detailed picture of what's going on in a given space," said Alanson Sample, associate professor of electrical engineering and computer science and a co-author of a paper presented recently at the iEEE RFID Conference in Phoenix, during an interview with the university's Michigan News newsletter.
This, Sample says, cold enable everyday items such as frying pans, pill bottles, yoga mats, coffee cups and countless other non-electronic objects to be turned into a network of Internet of Things sensors.
"Imagine a world where your pill bottle keeps track of your medication intake and a water glass monitors your hydration level," Sample also said. "Even your yoga mat is aware of your exercises and could adjust lighting, temperature and background music accordingly."
Sample says there could also be applications in elder care, where it could be used to unobtrusively monitor medications and daily activities, helping the elderly stay independent longer without the need for expensive and invasive live-in care.
The RFID labels will cost just a few cents each, Sample says. He also says IDAct can sense the presence and movement of people in a room and detect the movement of objects with enough detail to determine, for example, whether you've moved a pill bottle or cooked a meal.
"Given the ubiquity of these objects, there are significant opportunities in enhancing their sensing capabilities and creating interactive applications around them," said Hanchuan Li, a former graduate researcher in computer science and engineering at the University of Washington and lead author on the paper.
"Every object causes electromagnetic interference in a specific way," Sample added. "We can use that information, along with information from RFID tags, to get a very detailed picture of what's going on in a given space."
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These improved signals are then analyzed by a machine learning algorithm run by an on-site computer to infer what's happening in a room. In the testing phase, this processing was done on a laptop, but Sample envisions that the necessary hardware eventually will be integrated into the RFID reader itself.
The paper says tests showed the system accurately detected specific activities more than 96% of the time.
The team tested the technology by outfitting a volunteer's apartment with a series of RFID readers and then tagging household objects with RFID tags. They collected 26 hours of data from each room while users were present, and also collected two hours of data from empty rooms as a control.
RFID tags were attached to household items such as a knife, vacuum cleaner or pickle jar, and volunteers performed 24 activities including: blend a smoothie, roast chicken and potatoes, climb the stairs, mop the floor and brush their hair.
The data came from dynamic changes in received signal strength and received signal phase as objects were moved by the volunteers, or when the body of a volunteer changed the electromagnetic environment around stationary objects, or a combination of both – data made richer because the reader frequency-hops five times a second.
What's next? Sample says the team now plans to look for industry partners that could build out the technology for use in elder care settings. Sample and Li developed the technology with Shwetak Patel at the University of Washington and Chieh-yih Wan and Raul Shah of Intel Corp.'
Whether anyone wants a water glass that monitors your hydration level remains the key question, it seems, in these kinds of technology advances.
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