Using digital twins to enable AI control of building energy management | SPONSORED
Using digital twins, one can enable AI to better interpret and train algorithms to manage building energy. One of the greatest hurdles in use of AI is cleaning the data to train the algorithm well. Digital twins allow the user to engage with the data to ensure its validity prior to AI training, creating a more seamless transition to using intelligence to deploy solutions.
– Successful machine learning requires large amounts of data. In building terms that translates to 1000’s of sensors
– The building needs to be operated ‘correctly’ to train the ML effectively. With many interrelated building systems that is extremely hard using traditional dashboards
– Displaying all the data on a suitable digital twin of the building and adding helpful visualizations vastly simplifies the job of the human operator
– If alerts and errors do occur, they often ‘cascade’ through the building. Identifying the root cause is much easier on a 3D digital twin allowing much faster normalizing of the data used for training
Sponsored by UrsaLeo