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2020 was a year of reckoning for the IoT

January 5, 2021 by Stacey Higginbotham Leave a Comment

The biggest IoT story of 2020 was how much the internet of things struggled. From VentureBeat's deep-dive into Sigfox's challenges to the Wall Street Journal's story on Cisco's decision to end its smart city product, it felt like the media was … [Read more...]

Filed Under: Analysis, Featured Tagged With: BCG, libelium, Schneider Electric, Senet, Sigfox

Project CHIP releases draft specification just in time for 2021

January 4, 2021 by Stacey Higginbotham Leave a Comment

Project Connected Home over IP, or CHIP, the working group dedicated to creating a building standard for the interoperability of smart home devices, closed out 2020 by sending out a draft version of the spec to all of its member companies. Someone … [Read more...]

Filed Under: Analysis, Featured Tagged With: Amazon, Apple, google, Project CHIP, samsung

Let’s demystify the latest NIST IoT security releases

December 21, 2020 by Stacey Higginbotham Leave a Comment

Earlier this month, President Trump signed into law the 2020 Internet of Things Cybersecurity Improvement Act. The law calls on the government to purchase only security-connected devices and asks the National Institute of Science and Technology … [Read more...]

Filed Under: Analysis, Featured Tagged With: NIST, security

DIY smart home hubs are going retail: Here’s why that’s a good thing

December 16, 2020 by Kevin C. Tofel 1 Comment

For years, there have been two kinds of hubs that run smart homes. One is the kind you buy from a retailer, such as the Amazon Echo Plus, Hubitat, Samsung SmartThings, or Wink hubs. And one is the DIY kind where you download and install software to a … [Read more...]

Filed Under: Analysis, Featured Tagged With: Amazon, Apple, DIY, google, Home Assistant, Home Assistant Blue, HomeBridge, hubs, open source, raspberry pi, samsung, smart home

Researchers take a 3-pronged approach to Edge AI

December 14, 2020 by Stacey Higginbotham 3 Comments

Machine learning at the edge may be designed for tiny chips, but it is a huge topic. If we can run machine learning models on constrained devices, we can keep data local, which will boost privacy, and we can reduce the energy demands of both the … [Read more...]

Filed Under: Analysis, Featured

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