Artificial intelligence and machine learning will transform the IoT

In the IoT, AI and ML are going to enable whole new classes of applications and markets that were completely impossible or extremely challenging to develop before now. 

Technologically, using AI and ML in the IoT was traditionally way too complex, slow, and insecure. And commercially, the use of AI in IoT was simply too expensive: you needed costly high end processors and a team of data scientists just for starters. 

What’s transformed this is the development and advancement of 'tiny machine learning' or 'TinyML'. This enables ML to be performed on constrained-computation devices in a highly simplified way. The industry gold standard for running advanced AI and ML algorithms on resource-constrained devices typical of the IoT is TensorFlow Lite. 

In parallel, Nordic Semiconductor has constantly expanded the limits of what “resource constrained” means in battery-powered IoT with its nRF52, nRF53, and nRF54 Series Systems-on-Chips (SoCs). 

And when it comes to marrying high computing power to low power consumption. AI traditionally required a lot of computational processing that in turn burned a lot of power: more than could be supplied by batteries. 

Yet battery power is required to do anything useful in IoT. And this is where Nordic Semiconductor’s expertise in ultra-low power wireless with the use of high-end processors is now going to firmly come into play. In fact, Nordic is at the forefront of AI and ML in IoT and ready to enable any of its customers to take advantage of it. 

It’s now possible to develop AI and ML-powered applications that use battery-powered resource-constrained devices. Applications that multiple Nordic chips are capable of supporting – including both the nRF53 Series (nRF5340), and nRF52 Series nRF52840 and nRF52833. But without question, Nordic's latest nRF54 Series (both the nRF54H20 and nRF54L15) are exceptionally well matched for AI and ML due to the way they combine optimal-computational power with -power efficiency. 

nRF Edge Impulse
nRF Edge Impulse app is developed in collaboration with Edge Impulse to train and deploy embedded machine learning models on the Nordic Thingy:53 using Edge Impulse Studio.  Every Nordic Thingy:53 comes pre-installed with firmware compatible with the nRF Edge Impulse mobile app. The app allows you to upload raw sensor data via your mobile device to the cloud-based Edge Impulse Studio and deploy fully trained ML models to the Nordic Thingy:53 over Bluetooth® Low Energy (LE).

Features

Nordic Thingy:53

• The Nordic Thingy:53™ is an easy-to-use IoT prototyping platform. It makes it possible to create prototypes and proofs-of-concept without building custom hardware. The Thingy:53 is built around the nRF5340 SoC, our flagship dual-core wireless SoC. The processing power and memory size of its dual Arm Cortex-M33 processors enables it to run embedded machine learning (ML) models directly on the device

Application

The sensors on the Nordic Thingy:53 collect sensor data:

• Accelerometer
• Microphone
• Magnetometer
• Light
• Temperature, Pressure, Humidity and Air quality
• Inertial (Accelerometer and Magnetometer)
• Light and Environment
• Light and Inertial
• Environment and Inertial

Key components 

• Reduces design size: Replace multiple components with a highly integrated SoC requiring minimal external components.
• Prolongs battery life or reduces battery size: Efficient processing, ultra-low power radio, and minimal sleep currents.
• Provides long range: Best-in-class multiprotocol radio with 10 dBm TX power, -100 dBm RX sensitivity for Bluetooth LE and -104 dBm for 802.15.4.
• Protects against security threats: State-of-the-art security with secure boot, secure firmware update, secure storage, and protection against physical attacks.

Benefits

Why more is more in AI and the nRF54H Series 

Running AI and ML applications successfully on battery-powered wireless chips requires powerful computational capabilities at modest power consumption levels. Nordic's nRF54H Series offer the best of all worlds. You get multiple Arm Cortex-M33 processors that offer best-in-the-world levels of mobile computing power at the lowest possible power. 

This means you can do 10x as much data processing as you could in the past. Or do the same amount of data processing 10x faster and have the device rapidly go back to into ultra low energy sleep mode, and so use 10x less power. That’s the key. 

The nRF54H Series breaks the traditional tradeoff link between choosing either high computational power and high-power consumption, or low computational power and low power consumption. Now you can have high processing power and low power consumption: the lowest power on the market for AI and ML. 

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