The past 10 years have given us some truly innovative technology; now, healthcare providers are beginning to figure out the best ways to use it. They would do well to follow other industries by listening to consumers — in this case, patients—to determine the best way to incorporate this technology into their workflows.
This article is Part 2 of a three-part series that we are writing about work that Manifold did with one of our clients, Cortex Building Intelligence. In our previous post, we talked about finding edges in sensor signals so we could use them to help us estimate a building’s start time.
We want to find sharp transitions in the various HVAC sensors—rising edges for electricity, steam, and static pressure and falling edges for supply air temperature (SAT). It’s easy for a human to pick out edges—but how do we teach a computer to do it?
This article is Part 1 of a three-part series that we are writing about work Manifold did with one of our clients, Cortex Building Intelligence. Cortex’s vision is to use data-science to make commercial building heating, ventilation, and air conditioning (HVAC) operations more efficient.
Over the next few posts, we want to give you a look "under the hood” of our data-science operations. To that end, we’ll discuss how we solved one of the foundational problems at Cortex: figuring out when a building’s HVAC systems were turned on.