How iRobot used data science, cloud, and DevOps to design its next-gen smart home robots (cover story PDF)

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Provided by: TechRepublic
Topic: Innovation
Format: PDF

iRobot has used its new design, software, and data science strategies to expand into new areas, using an approach to the smart home that is different from its big tech rivals.

This download provides the magazine version of the article as a free PDF for registered TechRepublic and ZDNet members. You can also read the online version of this iRobot cover story.

From the story:

Watching iRobot's new vacuum tag-team with the company's latest robot mop to clean a room is to glimpse a Jetsons-like orchestration of the home of the future.

Seeing the two working together shows how smart home robots are starting to talk to each other, in this case through a technology called Imprint Link, and coordinate to be more effective without needing human involvement. But these two new bots, and the ones that will follow them, also represent the evolution of iRobot's approach to software, data science, and design.

Certainly, the Roomba S9 (the vacuum) and Braava Jet M6 (the mop) represent a breakthrough. Using Qualcomm processors, smartphone-level processing, more memory, and Imprint Link, the two robots work together. When Roomba gets back from a vacuum job, it lets the Braava know when to start. The two robots share maps of the home, and you can command them to tackle jobs and prioritize via iRobot's app.

Here's where you'd expect me to hit you with specifications and features like Roomba's new rubber brush with fletches to pick up larger debris, advanced 3D sensors, and for the S9 price of $999 and S9+ price of $1,299, the Clean Base Automatic Dirt Disposal -- a system that empties the robot and puts dust and debris into a bin. I might as well also mention the Braava Jet M6 price of $499, and that you can buy the Clean Base separately for $349.

But the far more interesting tale revolves around how iRobot, which is almost 30 years old and has sold more than 25 million robots, found a new focus and leveraged data science to become a significant player helping to decide how the smart home will operate. If you're going to promise consumers that they won't have to touch their Roombas or worry about vacuuming for months at a time, there's a lot of backend IT and architecture work, data science, and cloud computing behind the scenes. This data-driven and DevOps approach may just set up iRobot as a key smart home leader that can ride emerging trends such as aging in place.

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