In manufacturing, security, and construction, the ability to detect adverse sounds such as breaking glass offers valuable benefits, ranging from safety monitoring for workers in hazardous environments to quality control checks on production lines.

In this webinar, we will demonstrate how to quickly develop a glass-breaking detection system using Edge Impulse platform and the Arduino Nicla Voice device. We will cover the basics of training a machine learning model to identify particular sounds and how to deploy the model onto the Arduino Nicla Voice.

By attending this webinar, you will learn how to use these tools to create a system that can recognize specific types of sounds, and how to apply this technology in various industrial settings. Whether you are a developer, engineer, or researcher, this webinar is a valuable opportunity to learn about edge machine learning and its practical applications in an industrial environment.

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Speakers:
• Andrea Richetta, Head of the Pro Customer Success at Arduino