#6178 Case Study - Applying Machine Learning to Identify Impact of Covid on Energy Use

John Petze – Wed 29 Sep


We are excited to publish a new case study by the Energy Twin team demonstrating how they applied machine learning in SkySpark to detect and analyze the energy use impact of Covid related changes to building operations. During the pandemic, buildings were exposed to nonstandard regimes (reduced number of occupants, non-stop ventilation, total lockdown, etc.). Valuable data were measured by BMS systems. Analysis of these data provide valuable knowledge about the effectiveness of setback regimes.

It's a timely and informative application of SkySpark and ML techniques to support improved facility operations.

Find the case study - Evaluation of Covid 19 Impacts on Energy Consumption Using Energy Twin Machine Learning in SkySpark here