Google, A.I. and the rise of the super-sensor

#News(IoTStack) [ via IoTForIndiaGroup ]

Remember when the Internet of Things involved a trillion sensors? Turns out we may need only one.

In Google’s demo, it’s clear that the camera functions as a “super-sensor.” Instead of a flower-identification sensor, a bar-code reader and a retail-business identifier, Google Lens is just one all-purpose super-sensor with software-based, A.I.-fueled “virtual sensors” built in software either locally or in the cloud.
In the past four years, another revolution has disrupted the expected “trillion sensor world” revolution, namely the rise in cloud A.I., which changes everything. Instead of different, single-purpose sensors installed all over every vehicle, person, wall, machine and road, we’ll have general-purpose super-sensors, and their data will be used for software-based virtual sensors.
Why ‘synthetic sensors’ are better than real ones
Researchers at Carnegie Mellon University (CMU) last week unveiled their “super sensor” technology, which they also call a “synthetic sensor.”

The researchers have developed a board containing a small range of sensors commonly used in enterprise and commercial environments. The encased board functions like a single black-box sensor that plugs into a wall or USB power source and connects via Wi-Fi.
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.

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