This repo is related to the course of "Machine learning for IOT 2023/2024" in Polito.
What we did in this project
Develop ML pipelines for IoT applications
• Collect data with sensors
• Store & process data
• Train & optimize ML models for IoT data
• Deploy ML models at the IoT edge
• Implement edge-to-cloud/cloud-to-edge communication
Programming language:
• Python
Tools/IDEs:
• Visual Studio Code (local development)
• Deepnote (cloud development)
• Redis (cloud storage)
Use Case: Smart Battery Monitoring
• Remote monitoring of the Battery status of a connected Device
• The User can start/stop the monitoring using voice commands
• The User can visualize the Battery status over time from a Web Application
System Architecture
Homeork 1
1- Voice Activity Detection Optimization & Deployment
2- Memory-constrained Timeseries Processin
Homework 2
Training & Deployment of a “Yes/No” Classifier
Homwwork 3
1- Data Collection, Communication, and Storage
2- Data Management & Visualization