Complete system for the classification of Activities of Daily Living (ADL) by collecting inertial data from smartphones and evaluating supervised models (RF, SVM) under a Stream Learning approach, including online architecture for real-time classification.

Client-server backend for real-time Activity of Daily Living (ADL) classification. Handles window ingestion, prediction, label requests, and incremental model updates.