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Airborne Sound Maintenance in Remote Sites Using Low Power Federated Learning

Offered By: tinyML via YouTube

Tags

TinyML Courses Machine Learning Courses Federated Learning Courses Edge Computing Courses Industrial IoT Courses

Course Description

Overview

Explore a conference talk from tinyML Asia 2021 focusing on airborne sound maintenance in remote sites using low-power federated learning. Delve into the business and technical rationale behind selecting TinyML for Contextualized Airborne Sound in Predictive Maintenance. Discover how this solution aims to minimize operational downtime, reduce working capital for spare parts, and lower retrofitting expenses for existing machine infrastructure. Learn about the innovative approach using low-power sensors and federated learning to continuously improve the model while adhering to GDPR regulations. Gain insights into real-world industry examples, the concept behind the solution, and a demonstration of its implementation. Understand the background, vision, and edge processing involved in this cutting-edge application of tinyML technology.

Syllabus

Introduction
Why do companies see this as important
The problem
The concept
Examples from industry
Federated learning
Demonstration
Background
Vision
Edge Processing
Sponsors


Taught by

tinyML

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