Imagine a bottle of laundry detergent automatically connecting to the internet to place an order for detergent when running low on quantity, all by itself. Amazing, isn’t it? In a recent development, researchers from the University of Washington are working on making this experience a reality. They are aiming to develop 3-D printed plastic objects and sensors that can collect useful data and communicate with other WiFi-connected devices entirely on their own.

With CAD models that the team is making available to the public, 3-D printing enthusiasts will be able to create objects out of commercially available plastics that can wirelessly communicate with other smart devices. That could include a battery-free slider that controls music volume, a button that automatically orders more cornflakes from Amazon or a water sensor that sends an alarm to your phone when it detects a leak. According to the team, their goal was to create something that just comes out of any 3-D printer at home and can send useful information to other devices. But the big challenge is how to communicate wirelessly with WiFi using only plastic? That’s something that no one has been able to do before.

The system is described in a paper presented at the Association for Computing Machinery’s SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia.

To 3-D print objects that can communicate with commercial WiFi receivers, the team employed backscatter techniques that allow devices to exchange information. In this case, the team replaced some functions normally performed by electrical components with mechanical motion activated by springs, gears, switches and other parts that can be 3-D printed - borrowing from principles that allow battery-free watches to keep time.

Backscatter systems use an antenna to transmit data by reflecting radio signals emitted by a WiFi router or other device. Information embedded in those reflected patterns can be decoded by a WiFi receiver. In this case, the antenna is contained in a 3-D printed object made of conductive printing filament that mixes plastic with copper. Physical motion - pushing a button, laundry soap flowing out of a bottle, turning a knob, removing a hammer from a weighted tool bench - triggers gears and springs elsewhere in the 3-D printed object that cause a conductive switch to intermittently connect or disconnect with the antenna and change its reflective state.

Information - in the form of 1s and 0s - is encoded by the presence or absence of the tooth on a gear. Energy from a coiled spring drives the gear system, and the width and pattern of gear teeth control how long the backscatter switch makes contact with the antenna, creating patterns of reflected signals that can be decoded by a WiFi receiver.

For instance, as one pour’s detergent out of a bottle, the speed at which the gears are turning tells how much soap is flowing out. The interaction between the 3-D printed switch and antenna wirelessly transmits that data. Then the receiver can track how much detergent is left and when it dips below a certain amount, it can automatically send a message to the Amazon app to order more.

The team from the UW Networks & Mobile Systems Lab, 3-D printed several different tools that were able to sense and send information successfully to other connected devices: a wind meter, a water flow meter and a scale.

They printed a flow meter that was used to track and order laundry soap, and a test tube holder that could be used for either managing inventory or measuring the amount of liquid in each test tube. They also 3-D printed WiFi input widgets such as buttons, knobs and sliders that can be customized to communicate with other smart devices in the home and enable a rich ecosystem of “talking objects” that can seamlessly sense and interact with their surroundings.

Using a different type of 3-D printing filament that combines plastic with iron, the team also leveraged magnetic properties to invisibly encode static information in 3-D printed objects - which could range from barcode identification for inventory purposes or information about the object that tells a robot how to interact with it. It looks like a regular 3-D printed object but there’s invisible information inside that can be read with a smartphone.

The research was funded by the National Science Foundation, the Alfred P. Sloan Fellowship and Google.