New RFID System Could Turn Everything in Your Home into a Network of IoT Sensors

Imagine a world where your pill bottle keeps track of your medication intake and your water bottle monitors your hydration level. Even your yoga mat is aware of your exercises and could adjust lighting, temperature and background music accordingly. Surprisingly wonderful, isn’t it? A new RFID-based technology developed at University of Michigan could help make all this a reality. The new technology could help turn the non-electronic things in your home, like frying pans, bottles, yoga mats, cups and more into a network of IoT sensors.

The new system, called IDAct, bridges the gap between the estimated 14.2 billion "smart" electronic devices that are currently part of the Internet of Things and the hundreds of billions of everyday non-smart objects left out of the picture. U-M researchers say it's a key step toward creating a truly immersive IoT experience.

According to Alanson Sample, an associate professor of electrical engineering and computer science and author of the paper, IDAct: Towards Unobtrusive Recognition of User Presence and Daily Activities, which was presented recently at the IEEE RFID Conference in Phoenix, using RFID readers and battery-free RFID tags that cost only a few cents, 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. The tags can be attached to nearly any object in the form of a sticker, and RFID readers can be integrated into everyday objects like light bulbs.

According to Hanchuan Li, a former graduate researcher in computer science and engineering at the University of Washington and also a co-author on the paper, given the ubiquity of these objects, there are significant opportunities in enhancing their sensing capabilities and creating interactive applications around them. The technology accurately detected specific activities more than 96 percent of the time in a recent study. You could imagine assistive tools that could help the elderly stay in their own homes longer by monitoring their daily activities with this technology, explained Sample. It could detect changes in eating, sleeping or medication, for example, before the situation deteriorates and they end up in the emergency room.

RFID tags have been used for years to track objects in applications like shipping and theft prevention. The tags absorb just enough electromagnetic energy from the reader's signal to broadcast a simple, unique code. 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.

The IDAct system improves on this by providing a more nuanced reading of the signal from the RFID tags. It can 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.

According to Sample, every object causes electromagnetic interference in a specific way. This information can be used along with information from RFID tags, to get a very detailed picture of what's going on in a given space. These improved signals are then analyzed by a machine learning algorithm run by an onsite 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 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. They now plan 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 Shal of Intel Corp.

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