Exploring the IoT and TinyML with Blues Wireless
Machine Learning and the IoT are a match made in heaven. After all, IoT devices collect mountains of sensor data, what better way to uncover insights and actions than through sophisticated, modern computing methods like ML and AI? The problem is, leveraging ML with IoT has historically meant backhauling all your sensor data to the Cloud. When the cloud is involved, security is a concern, and in the realm of IoT, security is often a dirty word. In this workshop, you’ll learn how to leverage the power of Machine Learning on Edge Devices and build secure, cloud-independent IoT applications using the Blues Wireless Notecard. Attendees will have a chance to get hands-on with Blues tools and services and will walk away with Blues products and custom-built hardware ready for independent exploration of the IoT and TinML world.
- Session 1: Introducing the Blues Wireless Ecosystem - Lab 1: Claiming your first Device - Lab 2: Working with Sensor Data - Session 2: Why ML and the IoT - Lab 3: Building ML Models for Microcontrollers - Session 3: ML at the Edge with Microcontrollers (MCUs) - Lab 4: Inferencing on MCUs
Some experience with Python, ML with TensorFlow, and Arduino is nice, but not required. Please note the following (free) software must be installed to follow along with the hands-on components: - Chromium-based Browser (e.g. Chrome, Edge) - Visual Studio Code with PlatformIO Extension - Edge Impulse Studio Account (studio.edgeimpulse.com) - Node.js LTS - Edge Impulse CLI: npm install –g edge-impulse-cli