In the midst of a humid Hong Kong summer, Ambi Labs founder Julian Lee faced a dilemma.
“I have a 15-year-old husky, and if it’s too warm, he’ll bark,” says Lee. “So the conflict was do I keep on the air conditioning all the time and feel like I’m wasting a lot of energy, or do I worry about my dog suffering in the heat while I’m away?”
Lee’s quandary sparked the development of Ambi Climate, a cognitive platform designed to learn a user’s climate preferences and adjust indoor environments accordingly.
“We’ve found that factors other than temperature impact comfort, like humidity, sunlight in the room or even changing weather conditions outdoors,” says Lee. “Our system learns about and really accounts for these factors so that we help people get more comfortable in their homes and save energy at the same time.”
The solution’s machine-learning algorithms required powerful supporting technology, but as a startup business, Ambi Labs also needed a cost-effective hosting platform. To keep overhead low and operations lean, the company provisioned hybrid cloud infrastructure, running data-intensive workloads on SoftLayer bare metal servers hosted in Singapore.
Ambi Labs quickly and smoothly launched its innovative climate-control solution for an enthusiastic customer base in the Asia-Pacific region.
“A use case that’s particular to Asia is that the high humidity can bring on mold,” says Elizabeth Choi, Communications Strategist for Ambi Labs. “If our customers go on vacation, they can set a humidity threshold with the Ambi Climate solution, have the air conditioning turn on as needed, and come back to mold-free homes.”
With 450 million air-conditioned households worldwide, Lee anticipates wider global adoption of the Ambi Climate offering. “With IBM Cloud SoftLayer’s many points of presence, we’ll always be close to our customers,” he says.