How Generative AI Could Transform Consumer IoT – MIT Technology Review

The market for connected consumer goods is poised for renewed growth thanks to the emergence of generative AI and innovations in hardware and networking technologies.

In terms of technology, the Internet of Things (IoT) is old: The number of devices connected to the Internet exceeded the number of people on Earth around 2008 or 2009, according to a recent Cisco report. Since then, the IoT has been growing rapidly. Researchers say that in the early 2020s, estimates of the number of devices ranged from a few tens of billion to more than 50 billion.

But IoT is now enjoying an unusually intense new interest for a long-established technology, even one that is still experiencing market growth. A sure sign of this buzz is the emergence of acronyms like AIoT and GenAIoT, for “artificial intelligence of things” and “generative AI of things.”

What’s happening? Why now? Exploring the potential changes in consumer IoT may yield some answers. Specifically, the wide range of areas where the technology is being applied in the home and personal, from smart home controls to smart watches and other wearables to VR gaming—to name a few. The fundamental technological changes that are driving interest in this particular area mirror those in the IoT as a whole.

This story is available to subscribers only.

Don’t settle for half a story.
Get free access to current technology news.

You’ve read all your free stories.

MIT Technology Review offers an intelligent, independent filter for the flood of technology information.

Rapid progress converges on the edge

IoT is much more than a vast collection of “things,” such as automated sensing devices and connected actuators to perform limited actions. These devices clearly play a key role. A recent IDC report estimated that all edge devices—many of them IoT devices—account for 20% of the world’s current data generation.

But IoT is much more than that. It is a vast technological ecosystem that encompasses and empowers these devices. This ecosystem is multi-layered, although there is no single, agreed-upon taxonomy.

Most analyses will include in these layers the physical devices themselves (sensors, actuators, and other machines with which they directly interact), the data generated by those devices, the networking and communications technology used to collect, transmit, and receive information from the generated data to other devices or central data stores, and the software applications that use such information and other possible inputs, often to make suggestions or decisions.

The value of the Internet of Things is not in the data itself, but in the ability to leverage that data to understand what’s happening inside and around devices and then, when needed, use that information to recommend actions for humans to take or for connected devices to perform.

Download the full report.

This content was produced by Insights, the custom content division of MIT Technology Review. It was not written by the MIT Technology Review editorial staff.