Nordic Semiconductor has entered into a partnership with Edge Impulse, a provider of what’s termed as TinyML (or “tiny machine learning”) tools that are designed to run on resource-constrained semiconductor devices. Nordic also noted that all of its nRF52 and nRF53 Series Bluetooth Low Energy (LE) chips will now benefit from standard AI and machine-learning features. This is a first for the Bluetooth semiconductor industry.
“What AI and machine learning on resource-constrained chips does – which Nordic will now collectively refer to as TinyML – is take the application potential of wireless IoT technologies such as Bluetooth to a whole new level in terms of environmental awareness and autonomous decision making,” comments Kjetil Holstad, Nordic’s director of Product Management.
The main engineering areas for TinyML have included audio and vibration, where it can be used to establish normal operating patterns and rapidly detect anomalies. Example applications include anti-poaching (listening for gun shots), predictive and preventative maintenance (listening for tell-tale changes in the vibration signature of a public escalator or lift), and utilities (power line failure detection after a storm).
However, Nordic customer applications stand to benefit from TinyML in terms of asset-tracking to wearables.
“Although we have had customers build and run TinyML applications on Nordic’s Bluetooth chips in the past, before now this required quite a high level of mathematical and computer programming expertise using professional science industry and academia software like MATLAB,” Holstad added.
In terms of the Nordic Edge Impulse partnership, it will center around Edge Impulse’s Edge Optimized Neural (EON) compiler that is said to optimize computer processing and memory use by up to 50 percent when running TinyML on resource-constrained semiconductor devices.
“What our partnership with Edge Impulse will do is remove all the complexity and previous technological barriers-to-entry for our customers wishing to add TinyML features to their Bluetooth applications,” he said. “In fact, using Edge Impulse tools, Nordic customers could be up and running TinyML on their applications within an afternoon. And at an ultra-low power consumption level that still supports extended battery operation, even from small batteries.”
“What Nordic Semiconductor is doing through its partnership with Edge Impulse is bringing AI and machine learning to the wireless IoT masses,” says Edge Impulse co-founder and CEO, Zach Shelby. “By leveraging the fact that every Nordic nRF52 and 53 Series Bluetooth SoC employs at least one powerful Arm core processor on-board, and is architecturally designed for ultra-low power battery operation, this partnership is effectively democratizing access to state-of-the-art TinyML within the Bluetooth market.
Click to see the Edge Impulse Tutorials of continuous motion recognition, responding to voice and recognizing sounds from audio. You can also click to find Edge Impulse’s guide on nRF52840 DK and nRF5340 DK.
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