In other words, one small device functions as an all-purpose super sensor, which you can plug in and deploy for any sensing application. These sensors can detect sound, vibration, light, electromagnetic activity and temperature. The boards do not include regular cameras, largely to address concerns about user or employee privacy. You could also imagine a more powerful version that does include a camera.
As events occur near the sensor board, data is generated in specific, uniquely identifying patterns, which are processed by machine learning algorithms to enable the creation of a "synthetic sensor" in software.
Here's a simplified version of how such a sensor might work in a warehouse setting. You plug in one or a few super sensors. Then somebody uses a forklift. The resulting vibration, sound, heat and movement detected by the super sensor generate patterns of data that are fed into the system. You can identify this as "forklift in operation." (Further tweaking might determine not only when a forklift is in use, but where it is, how fast it's moving, how much weight it's carrying and other data.)
You can then program next-level applications that turns on a warning light when the forklifts are moving, calculates wear-and-tear on forklift equipment or detects unauthorized operation of forklifts.
The output from these "synthetic sensors" can be used by developers to create any kind of application necessary, and applied to semantic systems for monitoring just about anything.
The best part is that you could go in and create another "synthetic sensor" -- or 10 or 100 -- that detect all movement, activity, inventory, hazards and other things -- without any additional sensors.
A video produced by the CMU researchers showed applications in factories, offices, homes and bathrooms. For example, in the bathroom, it kept track of how many paper towels were used, all based on the sound produced by the paper towel dispenser. It could also monitor the total amount of water used there.
Again, the revolution here is not the ability to monitor everything. The revolution is to install a super sensor once, then all future sensing (and the actions based on that sensing) is a software solution that does not involve new devices, changing batteries or any of the other inflexible solutions imagined with the "trillion sensor world."
Imagine being able to buy cheap hardware that plugs into a wall, then from that point on all monitoring of equipment, safety, inventory, personnel and so on is done entirely through software. Going forward, there would be no need to upgrade sensors or IoT devices.
And get this: CMU's research is funded mostly by...Google!
The real power of A.I.
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