AI will drive IoT, says Silicon Labs in Embedded World keynote

  • October 10, 2024
  • Steve Rogerson

Artificial intelligence (AI) is the driver that will take the number of IoT devices over the billion mark in the next decade, according to Silicon Labs CEO Matt Johnson during a keynote address at this week’s Embedded World in Texas.

Silicon Labs (www.silabs.com) provides secure, intelligent wireless technology. It delivered the opening keynote for the inaugural Embedded World North America (embedded-world-na.com), with CEO Matt Johnson and CTO Daniel Cooley discussing how AI was driving a revolution in IoT.

“AI is rapidly becoming a key growth catalyst that will enable the number of IoT devices to reach over a 100 billion in the next decade,” said Johnson.

To realise this vision, IoT devices need to bring powerful upgrades in connectivity, compute, security, and AI and ML capabilities. Silicon Labs also revealed more information on the Series 3 platform that could make that a reality.

“Our upcoming Series 3 platform’s unparalleled capabilities and productivity will unlock new applications and new capabilities across a vast range of industries, from manufacturing and retail to transportation, healthcare, energy distribution, fitness and agriculture, helping transform each sector in remarkable ways,” said Johnson.

The full Series 3 portfolio will include dozens of products covering all major protocols and frequency bands, to connect just about anything. The first Series 3 device is designed to include a flexible IoT modem, capable of true concurrency on three wireless networks with micro-second channel switching.

A key driver in the IoT revolution is data, which flow between edge devices to the cloud and back again. This two-directional flow makes IoT edge devices ideal in the growing world of AI. Not only can the devices be used to make limited decisions at the edge, such as smart thermostats that assess ambient temperatures and adjust a home’s HVAC, but also with the advent of massive cloud-based AI applications. Edge devices can play a critical role as data collectors and apply their ML abilities to filter the valuable data from the chaff better.

AI operators value the ability to identify and transmit the data for the corner cases to make their systems more intelligent.