Explore the fundamentals of Edge Machine Learning, the benefits and steps needed to build a complete tinyML application.
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.
Industrial Automation Product Manager
Senior Applications Engineer
Client lead Software Engineer & Founder