Paper gets 'smart' with drawn-on, stenciled sensor tags !

A piece of paper is one of the most common, versatile daily items. Children use it to draw their favorite animals and practice writing the A-B-Cs, and adults print reports or scribble a hasty grocery list.

Now, connecting real-world items such as a paper airplane or a classroom survey form to the larger Internet of Things environment is possible using off-the-shelf technology and a pen, sticker or stencil pattern.

Researchers from the University of Washington, Disney Research and Carnegie Mellon University have created ways to give a piece of paper sensing capabilities that allows it to respond to gesture commands and connect to the digital world. The method relies on small radio frequency (RFID) tags that are stuck on, printed or drawn onto the paper to create interactive, lightweight interfaces that can do anything from controlling music using a paper baton, to live polling in a classroom.

"Paper is our inspiration for this technology," said lead author Hanchuan Li, a UW doctoral student in computer science and engineering. "A piece of paper is still by far one of the most ubiquitous mediums. If RFID tags can make interfaces as simple, flexible and cheap as paper, it makes good sense to deploy those tags anywhere."

The researchers will present their work May 12 at Association for Computing Machinery's CHI 2016 conference in San Jose, California.

The technology -- PaperID -- leverages inexpensive, off-the-shelf RFID tags, which function without batteries but can be detected through a reader device placed in the same room as the tags. Each tag has a unique identification, so a reader's antenna can pick out an individual among many. These tags only cost about 10 cents each and can be stuck onto paper. Alternatively, the simple pattern of a tag's antenna can also be drawn on paper with conductive ink.

When a person's hand waves, touches, swipes or covers a tag, the hand disturbs the signal path between an individual tag and its reader. Algorithms can recognize the specific movements, then classify a signal interruption as a specific command. For example, swiping a hand over a tag placed on a pop-up book might cause the book to play a specific, programmed sound.

"These little tags, by applying our signal processing and machine learning algorithms, can be turned into a multi-gesture sensor," Li said. "Our research is pushing the boundaries of using commodity hardware to do something it wasn't able to do before."