Developer resources

Learn more about Artificial Intelligence of Things, (AIoT) on Arm with the below resources. From keynotes covering the future of tinyML, to building autonomous robots during workshops, these resources provide deep-dive technical sessions about AIoT technologies. Jump to section:

Keynotes | Technical sessions | Workshops

Visit our YouTube playlist and watch all the AIoT Dev Summit tech talks and event highlight video.

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Endpoint AI for IoT

Explore the latest additions to the Arm AI platform: the Cortex-M55, Arm’s most AI-capable Cortex-M processor and the Ethos-U55, the industry’s first microNPU for Cortex-M.

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Keynotes

Giving developers the keys to building the future

Simon Segars, Jem Davies, John Fry, Arm and Kidus Asfaw, UNICEF

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Racing Robocars

Chris Anderson, 3D Robotics and
Rahul Ravikumar, DIY Robocars community member

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Democratizing innovation

Massimo Anzi, Arduino

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What is TinyML good for?

Pete Warden, Google

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Ethical AI

Timnit Gebru, Google AI

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Technical sessions

Scalable ML acceleration with ONNX runtime

Manash Goswami, Microsoft

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Running AI/Neural networks on microcontrollers made simple with the STM32Cube.AI

Markus Mayr, STMicroelectronics

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Maximize the performance of your ML platform with Arm software and tools

Ravi Mahatme, Arm

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Building noise-immune speech interfaces for IoT

Chris Rowen, BabbleLabs

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Pelion unified ID: the key to IoT at scale

Jerry Jun, Arm

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Scaling the market with mobile IoT and security by design

Ian Smith, GSMA

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A full Arm IoT stack from sensors to the cloud

Carl Perry, Packet

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Getting started with a self-driving RC car

Rahul Ravikumar, Google

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Extending ML to industrial IoT applications at the edge with AWS

Ian Perez Ponce, AWS

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Listen to your data: swim builds AI models and predicts in real-time

Dr Simon Crosby, Swim.ai

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From concept to production: design and optimize enterprise computer vision applications on embedded Arm devices

Dr. Nitin Gupta, Dori AI

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Ci in IoT/embedded: creating a simple scalable and automated workflow

Charles McCann, Arm

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Next generation ML for mobile and embedded platforms

Dr. Rajen Bhatt, Qeexo

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AI workflow for large scale deployment of far-edge ML devices

Mark Stubbs and Kabir Manghnani, Shoreline IoT

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How we got rid of passwords in IoT

Carel Grove, Arm

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Bootstrapping edge infrastructure for AIoT applications with open source software

Galem Koya, Canonical

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Robot Operating System (ROS): current and future capabilities on embedded systems

Katherine Scott, Open Robotics

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Workshops

Building end-to-end ML workflows with Arm

By Austin Blackstone, Neil Tan, Wei Xiao and Gian Marco Iodice, Arm

Machine learning workflows consist of tasks including data collection, aggregation, ML model training, evaluating, fine-tuning and model deployment. Arm not only provides processors that perform complex ML workflow locally, but also SDKs and tools that enable rapid application development and optimization, as well as services that orchestrate and automate the end-to-end ML tasks.

In this series of ML end-to-end workshops, we are going to introduce how to use Pelion Device Management and Treasure Data to train, validate and deploy your ML models, run and optimize ML algorithms on CPUs, GPUs, and NPUs with Arm NN and Arm Compute Library, and use ML frameworks to push machine intelligence to the tiniest Arm MCUs.

Building end-to-end ML frameworks for IoT/endpoint applications built with Arm Pelion Device Management, Data management, and Mbed OS:
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Building end-to-end ML frameworks for gateways built with Arm NN, Compute Library and Arm Cortex-A CPUs:
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TinyML application development for everyone

By Sandeep Mistry, Arduino

Step through sensor data capture, training, and model deployment to build an ML application, based on data that you will sample yourself. Learn how to use your gestures to train a classifier in TensorFlow and then deploy to an Arm Cortex-M-based board running Mbed OS.

This easy-to-follow workshop focuses on gesture recognition, but the sensor sources onboard the hardware provided, include accelerometer, gyroscope, color, Ambient Light, proximity, temperature, humidity, and pressure.

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Privacy-focused voice AI in intelligent robotics

By Samreen Islam, Carlos Chacin and Alfred Gonzalez-Cuzan, MATRIX Labs

We are at a point in time when voice AI is integrating seamlessly into our lives. We have them in our homes, on-the-go through our phones, and increasingly embedded into our everyday devices- headphones, cars, and TVs to name a few.

It should come as no surprise that voice-control for robots is also becoming increasingly popular due to its hands-free and potentially conversational nature, whether it be with a humanoid, robot arm, or autonomous rover. This workshop goes over how you can easily employ a privacy-focused voice assistant, Snips, with MATRIX devices, an edge, and IoT development platform that is powered by Arm microcontrollers and Xilinx FPGAs, to quickly deploy an effective voice-enabled robot of your choice, complete with sensors, feedback loops, and motor control.

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Get started with drone development on PX4

PX4 is the open-source flight control stack for drones, rovers and other autonomous robots. It's the de-facto standard for open source drone development. In this workshop, you will see the different components of a standard quadcopter, then use developer tools and SDK to do basic programming to enable the drone to be an IoT device and intelligent sensor platform. This workshop was delivered by Auterion and NXP.

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Agora – develop, deploy, and maintain devices profitably

By Garrett LoVerde, Embedded Planet

Embedded Planet introduces a general-purpose hardware platform and guide to deploy application-specific IoT devices on budget and on time. Agora is a multi-connectivity, multi-sensor IoT development platform that enables prototyping of Cellular, Bluetooth, and LoRaWAN applications. It also has seven sensors.

During this workshop, learn how to:

  • Ease development with a versatile MCU-based IoT hardware platform that is driven by Mbed OS
  • Develop intelligent applications that transform environmental factors such as temperature humidity, air quality, audio, proximity, and force into Information
  • Discover the value add for business utilizing this information
  • Go to production immediately with the preconfigured subset of the development kit that most closely meets your application need
  • Go to production at scale with a fully customized subset of the development kit that matches your application need most optimally

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End-to-end security with Arm-based edge devices and IoTeX blockchain

By Raullen Chai, IoTeX

Trusted Tracker is a GPS and environmental tracking device, developed by IoTeX with Arm TrustZone and CryptoCell technology. This workshop provides an overview of the hardware components of Trusted Tracker with an Arm Cortex-M33 processor with Arm TrustZone and Arm CryptoCell-310 security subsystem, Connectivity module (LTE-M, NB-IoT), and sensors. It introduces the high-level design of IoTeX blockchain, including system architecture, trusted computing framework, smart contracts, and core APIs and then showcase end-to-end security architecture of Trusted Tracker.

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Secure IoT with Mircochip and Kinibi-M

By Richard Hayton, Trustonic

In this session, you learn how to program a MicroChip SAML11 microcontroller to generate secure messages that a server or cloud can validate came from your device and can decrypt and display. The session covers an introduction to Kinibi-M and the steps that are required to write the Secure on-device code to talk to your PC or a provided cloud service.

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Unlock the potential of IoT security with Microsoft's Azure Sphere

By Brian Willess, Avnet

As billions of new devices are connected, organizations need to secure them to help protect data, privacy, physical safety, and infrastructure. In this hands-on Azure Sphere workshop, you can learn how this new security solution has integrated hardware, software, and cloud to provide a turnkey solution for IoT devices.

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Build your own Harry Potter wand with TensorFlow Lite Micro

By Pete Warden (Google), Kirk Benell and Rob Reynolds (SparkFun) and Scott Hanson and Arpit Shah (Ambiq Micro)

This is an experiential workshop that focuses on the use of TensorFlow Lite on a low-power microcontroller to perform machine learning. Modalities that are covered include word recognition in speech; gesture recognition using accelerometer values; and human presence detection using imagery.

The workshop covers machine learning model training, deployment, and operation, with a majority of time that is spent on a gesture-recognition activity, “Magic Wand”, that is based on the content of Pete Warden’s book, TinyML: Machine Learning with TensorFlow on Arduino and Ultra-Low-Power Microcontrollers.

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Containers in an IoT world: how Docker can make it easier to deploy your application on an edge device

By Jenny Fong (Docker) and Maurizio Caporali and Alessandro Genovese (SECO)

The growth of Arm-based devices in recent years is exponential. Last year alone, Arm, and its partners have shipped 23 billion Arm processors. With such growth in Arm devices, IoT and embedded software developers are looking for easier and more scalable ways of creating portable code which can be deployed easily on different platforms while reducing the time to market.

With the partnership between Arm and Docker, it is now possible to easily build and deploy containerized applications everywhere from edge to cloud, this allows software developers to scale from a PoC to a manageable and robust IoT solution.

During this workshop you will gain hands-on experience in developing and deploying a reusable Docker application on an IoT device. You will also learn about specific benefits containerization has over more classical software development approaches.

Ahead of accessing the workshop,  please complete this survey by SECO.

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AI on Adafruit's edge badge

By Alex Glow, Hackster

Watch this video and play with the Adafruit Edge Badge! This demo will show the "Micro Speech" demo — using TensorFlow with Arduino.

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Changing the landscape of AIoT

Artificial Intelligence of Things, (AIoT) is a combination of AI and IoT to achieve more efficient and smarter connected technologies. The term AIoT is the convergence of these two technologies helping to take artificial intelligence into all commercial and social sectors, enhancing business operations and making our world more efficient.

Watch the panel session with industry experts to see how we can change the landscape of AI and IoT together.

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Arm Innovator Program

Stay in touch and do not miss out on future events. Get access to more AIoT resources from Arm and our ecosystem partners.

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Arm AIoT developer contest

Join the AIoT Dev Contest for the chance to win $3,000 in cash and $1,000 in Ponoko credits. Share with the developer community what you have learnt about AIoT on Arm, and how this can be used to solve real-world problems in innovative ways.

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