This allowed us to have more precise control of the systems and also started to eliminate some of the downsides of using air-based control systems.
Connecting different brands and systems is much more seamless, and we can provide just about any type of control configuration as long as we have the data and sensors..
Instead of optimizing based on weather and occupancy, machine learning will allow us to optimize our buildings based on the weather forecast and the learned habits of our tenants.
my phone will pop up the time it takes to get there only on Friday, yet every other day of the week it has my work location as my leaving destination.
Being connected to the grid and able to talk back and forth, we will start to see dynamic load management and peak demand reduction as more automated and seamless process.
AI will allow us to forecast ahead of time and be aware of estimated surges days before they happen and adjust without human interaction..
Detailed monitoring of lighting conditions, IAQ, occupancy, and productivity will allow dynamic changes that care equally about occupant's well-being not just their comfort.
we can have true estimate in time of where our power is coming from and the impact our building is having on the environment and grid.
With the rapid rise in machine learning, now is the time to start reading and learning about the various technologies coming.
He is the manager overseeing the building analytics platform where he supports Piedmont Service Group and CMS Controls with optimizing or continuous commissioning through analytics...
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