Enabling Intelligence at the Edge with STWIN and NanoEdge™ AI Studio
From datalogging to embedded intelligence: using the SensorTile Wireless Industrial Node with NanoEdge™ AI Studio
Virtual hands-on workshop with live tech support
ST's SensorTile Wireless Industrial Node (STEVAL-STWINKT1B or "STWIN") is a development kit and reference design that simplifies prototyping and testing of advanced industrial IoT applications such as condition monitoring and predictive maintenance.
In this workshop you'll learn how to perform datalogging from the STWIN's on-board digital microphone using the FP-SNS-DATALOG1 software package, then use the data, export it to a PC, and import it into NanoEdge™ AI Studio to train an AI model. The trained model inference will then be executed at the Edge on the STWIN itself.
The datalogging procedure described will be applicable to all other time series sensor data and can be used as a blueprint to build a predictive maintenance application.
This workshop is self-paced and can be accessed on-demand any time after the start of the selected session (see Session dates and times). Please note that live tech support via break-out rooms will be available during the scheduled session hours.
Who should attend?
This workshop is intended for hardware and firmware engineers developing IoT nodes, home appliance and automation systems, industrial controls, medical devices, and wearable products.
This workshop is open to residents of the Americas only.
An STEVAL-STWINKT1B development kit is required to participate in the workshop exercises. Exclusively for attendees of this workshop, a limited number of free kits will be available with attendees responsible only for shipping cost. You will receive purchase instructions by email soon after we receive your request to participate.
You will learn
- About the SensorTile Wireless Industrial Node (STWIN) board and its sensor capabilities
- How to capture real-time DTMF audio samples using the STWIN on-board digital microphone
- How to utilize NanoEdge™ AI Studio to train AI DTMF audio classification models
- How to test the AI DTMF classification firmware on the STWIN in real time
- A PC or laptop running the 64-bit version of Windows® 10, with administrator rights for software and driver installation
- An Android (6.0 or higher) or iOS (13.0 or higher) mobile phone
- One STEVAL-STWINKT1B development kit
The use of two screens is recommended so that you can watch, pause, and rewind the instruction video on one screen while completing the workshop on the other.
Session dates and times (US Eastern Time)
|Session 1||Tuesday, 16 Nov 2021||1:00 pm - 4:00 pm ET||Online||Full|
|Session 2||Thursday, 18 Nov 2021||1:00 pm - 4:00 pm ET||Online||Full|
Meet your instructors
|Ernesto Manuel Cantone |
Manuel is Product Marketing Manager for MEMS and Sensors in the Americas. Starting his career as a mixed-signal IC designer, he promotes ST's IoT ecosystem to help developers succeed in Smart Industry, Smart City, Smart Home and Smart Things and to ensure that ST offers the latest Cloud, Connectivity, and Sensor Fusion building blocks for these markets. He earned his MS in Electrical Engineering from the Universita' di Pisa, Italy.
|David Kwak |
David is an Applications Engineer supporting ST’s MEMS sensors and cloud connectivity platforms. He joined ST in 2011 and has extensive experience with embedded system development and embedded software. He graduated from McGill University with a Bachelor of Engineering in Electrical Engineering.
|Markus Mayr |
Markus is Product Marketing Manager for Microcontrollers in the Americas West Region at ST, a position he has held for 5 years. In the semiconductor industry for over 25 years, he began his career at ST as a Microcontroller FAE in Munich, Germany. He later moved into a marketing and business development role, which brought him to the US in 1999. Markus earned a bachelor's degree in Electrical Engineering from Furtwangen University (HFU), Germany. He is currently based in Santa Clara, CA.
About the hardware and software tools you will use in this workshop
The SensorTile wireless industrial node (STEVAL-STWINKT1B) is a development kit featuring a core system board with a range of embedded industrial-grade sensors and an ultra-low-power MCU for vibration analysis of 9-DoF motion sensing data across a wide range of vibration frequencies, including very high frequency audio and ultrasound spectra, and high precision local temperature and environmental monitoring.
The FP-SNS-DATALOG1 STM32Cube High Speed Datalog function pack implements a High Speed Datalog application on STWIN evaluation kits. It provides a comprehensive solution for saving data from any combination of sensors and microphones configured up to the maximum sampling rate.
NanoEdge™ AI Studio is a new Machine Learning (ML) technology that brings true innovation easily to end-users. In just a few steps, developers can create an optimal ML library for their project, based on a minimal amount of data. NanoEdge™ AI Studio, also called the Studio, is a PC-based push-button development studio for developers that runs on Windows® or Linux® Ubuntu®.