For the “Internet of Things” to thrive, all it needs is for all devices to get along–which is currently wishful thinking. Last week, however, Google announced a partnership with Carnegie-Mellon University, which is leading a collaboration of faculty from several other academic institutions on a project to jumpstart the Internet of Things revolution. Their plan: Build a universal platform that lets any device talk to any other device. And fittingly, that master-key solution will be open source.

The problem is that IoT software and devices are mostly proprietary, built by each company and working well within their own sandboxes, but they don’t communicate well together. The joint project between CMU, Cornell, Stanford, Illinois at Urbana-Champaign, and Google wants to wipe away the private-industry middlemen that keep sensors in separate sandboxes by creating a new, open platform: GIoTTO.

The CMU team leader, Anind Dey, and his fellow professors are building GIoTTO’s middleware, which is a pretty technical job—stitching all the right software together so any sensor you pick up off the shelf (measuring temperature, pressure, light, etc.) will work with your system. Dey wants their platform to receive info via any signal type—whether BLE, passive infrared, or otherwise—and show people that info in ways they’ll understand.

To do that, Dey and his team will make a lot of proof-of-concept examples to test their tech, building sensor networks on campus to make the campus a “living laboratory” for people to discover IoT and come up with ways to apply the world of IoT to their field of study. The expansion across campus (and potentially out into the city of Pittsburgh) has three goals: Discover different use cases as diverse people outside Dey’s labs play with the IoT sensors, drive iterative development of GIoTTO’s open infrastructure by adapting it to those different use cases, and allow more people to experience the Internet of Things and study how they use it.

Dey’s team will also be teaching undergraduate and graduate courses on the future of IoT (and maybe plucking choice ideas from crafty students). The courses aren’t just in computer science: Dey’s team is a collection of seven computer science and engineering professors (and their postdocs and graduate students, bringing the team size up to about 50ish people) specializing in hardware, machine learning, and human-computer interaction. But because CMU is a democratic campus—very few things are pushed on faculty from on high–Dey’s team can’t just spread sensors willy-nilly on other departments’ turf. The plan: Publicly display some sample end-user applications that demonstrate what you can do with sensor-collected data, and wait for word of mouth to spread. Eventually, Dey hopes, other departments will come asking Dey’s team for a sensor cluster of their own.

“There will be a ton of different objects going into our infrastructure—so we want to be able to query them. We want to be able to ask any sensor and pull or subscribe and tell me when something interesting is happening,” says Dey. “Our idea is that I as an end user do not understand what readings of barometric milligrams of mercury mean. What I want to be able to do is take a barometer and put it on my wall, open and close my window 10 times, and not get a response in terms of pressure—instead, I have a sensor that tells me whether my window is open or closed.”

The sensors themselves measure basic environmental information–temperature, proximity, barometric pressure, seismic or vibration activity, light–but Dey’s team will be able to draw activity conclusions from multiple readings. For example, the proximity sensors can track how many people are in an area or in line for an event, while a temperature sensor could tell the team if someone switched on a new pot of coffee. The type of sensor isn’t terribly important to the experiment, says Dey: His team is really just excited to hear what other departments want to track, and Dey’s team will finagle a way to track it using available sensors. With such a liberal and technologically aware population, Dey is sure there will be uneasiness about data tracking. Until their project’s data collection becomes a norm, Dey’s team will put up signage to indicate what data the sensors are collecting and where it is being collected.