Real-time NYC subway anomaly detection: GTFS-RT, online ML (River), live Mapbox command center tracking 1000+ stations.
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Updated
Apr 17, 2026 - Python
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river-ml
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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.
machine-learning scikit-learn human-activity-recognition incremental-learning smartphone-sensors stream-learning river-ml
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Feb 12, 2026 - Jupyter Notebook
Client-server backend for real-time Activity of Daily Living (ADL) classification. Handles window ingestion, prediction, label requests, and incremental model updates.
data-collection human-activity-recognition sensor-data real-time-ml stream-learning adl-classification river-ml
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Feb 12, 2026 - Python
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