Video Material

EML-301: Add Predictive Maintenance to Smart Building Devices with TinyML

Overview

SensiML, a company known for having pioneered software tools simplifying the development of tinyML code for IoT sensor applications, demos the process for building an IoT edge device.

Whether it's predictive maintenance for climate control systems, AI-enabled access control, or smart lighting sensors, advancements in machine learning at the IoT edge (i.e., tinyML) present us with great opportunities to redefine the whole smart building concept.

During this session, SensiML uses the Thunderboard Sense 2 to demonstrate what tinyML technology can do to help differentiate your smart building device and application and how you can up your game with little to no data science expertise!

By the end of the session, you will have surveyed several noteworthy tinyML smart building use cases, seen a working HVAC predictive maintenance application, and followed a step-by-step process for building this example application.

Moderators

Paul Daigle

Industrial Automation Product Manager
Silicon Labs

Manasa Rao

Senior Applications Engineer
Silicon Labs

Speakers

Chris Rogers

CEO
SensiML

Chris Knorowski

CTO
SensiML

Craig Babcock

Client lead Software Engineer & Founder
SensiML

Duration

1 Hour, 45 Minutes
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