We held our next tinyML Talks webcast. Chris Knorowski from SensiML presented Build an Edge optimized tinyML application for the Arduino Nano 33 BLE Sense on May 11, 2021.
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Building a tinyML application touches on skill sets ranging from hardware engineering, embedded programming, software engineering, machine learning, data science and domain expertise about the application you are building. The steps required to build the application can be broken into four parts:
• Collecting and annotating data
• Applying signal preprocessing
• Training a classification algorithm
• Creating firmware optimized for the resource budget of an edge device
This talk will walk you through all the steps, and by the end of it we will have created an edge optimized TinyML application for the Arduino Nano 33 BLE Sense that is capable of recognizing different boxing punches in real-time using the Gyroscope and Accelerometer sensor data from the onboard IMU sensor.
Chris Knorowski is the co-founder and CTO at SensiML where he builds tools to make it easier for developers an engineer’s create smart sensor algorithms capable of running at the extreme edge. Prior to SensiML he worked as software engineer and data scientist at Intel and Dupont Pioneer. He holds a Ph.D in computational physics from Iowa State and a B.S. in Physics from Virginia Tech.
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Watch on YouTube:
Chris Knorowski
Download presentation slides:
Chris Knorowski
Feel free to ask your questions on this thread and keep the conversation going!