Sapient uses machine learning techniques to understand the "state" in which a particular device is in. For example, Sapient understands the difference between a laptop that is being used by a person vs a laptop that is idly charging vs a laptop that is fully charged, or more simply, Sapient can tell when a lamp is on or off. With this insight into every device in the building, Sapient makes inferences about what it means for certain devices to be "in use" in a particular region.

Below is visual example of the result of Sapient's analysis for three example devices over the course of three days.

After performing this analysis, a new understanding of how your space is used is now possible. Take for example the laptop computer, the space heater, and the computer monitor seen above, and lets assume they're all found in the same room/workstation. Sapient will assume that any time the laptop computer OR the computer monitor are "in use", that the room/workstation is occupied, but NOT occupied if the space heater alone is "in use".

The space heater is ignored for occupancy purposes because some equipment types are more telling of occupancy than others. Things like space heaters, refrigerators, and lamps are not very good at implying occupancy, and so they are ignored; however, if you are interested in a comprehensive understanding of equipment usage optimization and you care less about whether a person is actually present, then the usage of space heaters, refrigerators, lamps and more should be considered.

Below is a visualization of exactly that.

For an interesting article on how Sapient created this technology, check out our blog post on the subject. 

Did this answer your question?