Combine big data with weather information
The amount of properties being led by data in Finland is still small. We are doing our best to change that.
LeaseGreen’s digital team has developed its own algorithm for controlling property automation that takes advantage of the big data produced by the properties and AI. By using historical information, the use profile of the building, real-time data provided by sensors in the property and weather forecasts, heating can be controlled so that we can predict the necessary requirements.
Predict power demand and upcoming hardware issues
As freezing temperatures approach, heating starts earlier than normal to avoid peak output. During a hot summer, the building is cooled at night, not when the temperature is already becoming unbearable.
The function is planned and is executed remotely. Maintenance staff do not need to run to the property to make hasty adjustments. Data suggests when equipment might be going wrong before it finally breaks.