Smarter Edge Equals Smarter Living Using AIoT

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www.eetimes.com, Dec. 28, 2022 – 

When smart homes began growing in popularity at the turn of the century, living smart meant using internet-connected devices with clever features. Two decades later, smart living has entered a new era of intelligent devices on the edge that are increasingly designed to make decisions. That's according to the experts who spoke during a November panel talk titled "How Smart Can We Live?" as part of the Embedded Forum at electronica 2022 in Munich. Nitin Dahad, editor-in-chief of embedded.com, moderated the session.

"Smart devices started off with a lot of what now would be categorized as clever features," said Ali Osman Ors, director of artificial intelligence and machine-learning strategy and technologies for edge processing at NXP Semiconductors. "Now we're moving into the new definition where 'smart' means you have a lot of info coming from a very wide range of inputs coming to these devices, and with all of these inputs and data, the devices make a decision by themselves."

With the addition of robots and AI, the internet of things has become the artificial intelligence of things (AIoT) and edge devices are often intelligent even when not connected, said Pier Paolo Porta, marketing director for Ambarella.

The emerging AIoT expands capabilities by providing distributed intelligence with endpoints capable of decision-making, said Suad Jusuf, senior manager at Renesas Electronics.

"We are not talking anymore about smart being [only] capable of providing data to the cloud, being always connected, but also a system that is capable of making its own decisions – for example, within the predictive maintenance arena," he added.

As an example of this edge intelligence, advanced home-security cameras now can be trained to learn the faces of frequent visitors and alert residents when one of those familiar people approaches the front door or any door with a security camera.

At Renesas, "we have managed to establish multi-modal, vision-based, camera-based face recognition on a relatively simple M4 core Renesas device," Jusuf said.

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