TinyML : Let’s Put Some Intelligence Into IoT!
In this session, we will review what IoT traditionally has been and where it is today, what Machine Learning is and how the two technologies overlap to form the basis of edge intelligence & TinyML. We will discuss the advantage these technologies have over other more traditional approaches, share some of the many applications, and how to get started by walking through a few real-world examples. We will demonstrate using public data sets, but also the entire lifecycle from data ingestion using sensors to model creation/training, deployment, and then finally some predictions on the device. The presenter will be using sensor data and executing code on an Arduino Nano 33 BLE Sense device ( https://store-usa.arduino.cc/products/arduino-nano-33-ble-sense ). Additionally, as a group, we will walk through an interactive workshop where the audience will use their smartphone and an account with Edge Impulse to showcase intelligent IoT devices in action.
1. Define IoT 2. Define Machine Learning 3. Define Edge Intelligence & TinyML 4. Discuss common use cases 5. Case Study - Arduino Nano BLE Sense 33 6. Edge Impulse - Group exercise with your Smartphone 7. Summary/Wrap Up
1. Laptop 2. SmartPhone 3. Ardunio Nano 33 BLE Sense or Sparkfun Edge (Optional - can just ride shotgun and watch the presenter if you wish) 4. Docker 5. Edge Impulse Account
- Capturing Data from the Physical World
- Training a Machine Learning Model
- Intelligence on IoT Devices