iMTED’s AI energy assistant detects operational irregularities and hidden inefficiencies in non-residential buildings by utilising existing data from energy and water meters. Its physics-based neural networks enable energy cost savings of up to 20%, real-time anomaly detection and load forecasting, without the need to install new sensors or incur significant capital expenditure.
