ITAIPU Binacional presents its approach to continuous equipment health monitoring using AVEVA PI System and advanced machine learning models. By integrating SCADA/EMS and CMMS data, the team developed internal tools to calculate health indices and predict failures using algorithms like Long Short-Term Memory (LSTM) and Random Forest. Real-time insights are visualized in AVEVA PI Vision, enabling condition-based maintenance and smarter asset management across generation and transmission infrastructure.