Google Acquires Nest: Big Data Comes to Energy

by Michael Hausenblas on Feb 04, 2014 |

Google has acquired Nest for $3.2 billion in cash. Nest produces smart thermostat and smoke detectors, and with this acquisition Google turns Nest's devices into another major data source that will help Google understand how people live.

Tony Fadell (CEO of Nest) stated it in the official announcement:

We’re thrilled to join Google. With their support, Nest will be even better placed to build simple, thoughtful devices that make life easier at home, and that have a positive impact on the world.

There are speculations about what Google will do with the data Nest collects from its sensors: from combining it with its social data (Google+) to re-selling it to interested parties such as energy providers or insurances. Forbes reports that Google has already gathered experience in this very domain: on the one hand with EnergySense, its own smart thermostat project, and on the other hand back in 2009 when Google launched a web-based energy management tool called PowerMeter, which was shut down in 2011.

Beyond what Google is planning with Nest and its data, others have as well spotted an opportunity around the Nest acquisition, for example Spark Integration Technologies, an M2M and devices integrator, who provided a do-it-yourself version of the Nest Learning Thermostat as open source only days after the acquisition announcement. And while the Nest acquisition is certainly the one with the highest price tag it is by far not the only one in the realm of Internet of Things investments: only six month earlier, ARM acquired Sensinode and with it Zach Shelby, one of the main drivers of standardising IoT protocols such as 6LoWPAN.

Google is unlikely to stop its shopping tour anytime soon, though, or as David Schubmehl (research director with IDC) puts it:

In a broader pattern, if Google is focusing on artificial intelligence (AI) and machine learning, how is this kind of semantic understanding going to help us make decisions faster and do our jobs. We're still a ways away from (real AI). It's more about putting 10 to 15 connections together to help me handle a thinking process and make decisions faster.

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