The Nest: A thermostat that's eager to learn in order to help you save

November 1, 2011 By Matt Hickman

Just in time for the high season of thermostat tweaking comes a nifty, energy-saving household gizmo with some serious tech cred: The Nest Learning Thermostat from Nest Labs, a Silicon Valley startup partially funded by Google Ventures and founded by none other than the "father of the iPod" himself, Tony Fadell, an Apple expat who designed the original iPod along with Matt Rogers, a fellow erstwhile Apple staffer who served as engineer of both the iPod and iPhone.

Although there are a handful of other customizable digital thermostats geared to help consumers reduce heating and cooling bills, Nest Learning is the first that I've seen that actually learns a user's habits and preferences and adjusts a household's temperature accordingly. The device is capable of remembering your personal schedule and heating/cooling idiosyncrasies within just a week and then programs itself to save energy while you're away, continuously refining itself to adjust to your unique schedule of coming and going - no matter what the season.

Achieving its thoughtful braininess through a combination of sensors, algorithms, machine learning and cloud computing, the Nest may seem like a frustratingly complicated gadget, but its developers promise that the sleek - and dare I say, sexy - little device is a breeze to install and use. And, naturally, the Nest can be connected to a home wireless system, allowing you to adjust temperature settings and check daily through an energy history feature from a PC, smartphone or tablet. The device also provides tips on how to make energy-wise decisions around the house and tells you, through the nifty Nest Leaf feature, when you're actually . My favorite feature? A that illuminates the device's when you approach it, eliminating any fumbling-around-in-the-dark thermostat mishaps.

Here's what Fadell had to say about his creation:

"It was unacceptable to me that the device that controls 10 percent of all energy consumed in the U.S. hadn't kept up with advancements in technology and design. Together with the team, co-founder Matt Rogers and I set out to reinvent the thermostat using advanced technologies, high-quality manufacturing processes and the thoughtful design elements the generation has come to expect. The resulting Nest Learning Thermostat is like no other thermostat on the market. We hope it will not only save money and energy, but that it will teach and inspire people to think more about how they can reduce home-energy consumption."

Amen. Apparently, according to the American Council for an Energy-Efficient Economy, a whopping 89 percent of homeowners with programmable thermostats installed in their homes neglect to use them on a regular basis because they find them too complicated. The team at Nest Labs wants to change that.

The PVC- and mercury-free Nest Learning Thermostat is currently available for pre-order and will hit retailers such as Best Buy in mid-November with a suggested retail price of $250. It's compatible with HVAC systems and can be installed within 20 minutes as a DIY project or professionally. With the holidays just around the corner, the Nest could prove to be the perfect gift for the tech-obsessed thermostat tweaker in your life.

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not rated yet Nov 02, 2011
I once had to develop a thermostat in software for an industry process. There were a few inputs, some of which were "before" the heater in the process. This boss couldn't understand that it was hard.

He finally got it when I had a professor from the local technical university call him explaining that they have an entire sub-department for this kind of thing only.

Yes, the mundane and ultra-trivial thing, called thermostat, is really unbelievably hard to improve on, especially if you want more than marginal results.

And yet, there are dozens of this kind of circuits in the brains of animals. Without these, you couldn't run, jump, throw, ride bicycle, play tennis, and especially juggle a stick on your fingertip.

It amazes me why this particular problem seems to be so hard.

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