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August 2017
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The Edge is Here. It’s Here Now. Part 2

Analytics & Learned Actions Move to the Edge

Marc PetockMarc Petock,
Chief Communications Officer,
Vice President,
Marketing
Lynxspring &
Connexx Energy

Contributing Editor

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Last month I wrote about how the Edge is contributing to a significant shift in the way we are acquiring information, interacting with it, and making decisions.

Continuing this theme, this evolution has been enabled, in large part, by rapid advances in lower-cost controllers, open source software, powerful processors -and the world of IoT. This combination is also changing our BAS landscape to support a decentralized architecture where analytic processing can be done at the edge.  This evolution is also changing the execution of analytics and machine learning's location.

With more devices at the edge comes more data that has the potential to provide enhanced insights into how we manage and operate facilities. At the same time, it also presents a new challenge for how to analyze it all. Collecting and compiling this data benefits no one unless there is a way to understand it all. Making sense of huge amounts of data is a perfect application for learned actions.

By applying analytics to machine learning at the edge, we can identify and understand patterns, make more informed decisions and initiate action. This leads to a variety of benefits for building operators and system integrators such as proactive intervention, intelligent automation, and highly personalized experiences. It also enables us to find ways for these devices to work better together, make building automation systems easier to use, extend the lifetime value of the equipment within these systems and deliver a more personalized environment for occupants.

Edge analytics and machine learning can enable autonomous improvements to operations within a facility — including heating, cooling, and lighting. For example, we can identify and automatically act upon usage patterns in a building space such as recognizing specific patterns ranging from people in the room, room temperatures to controlling lights on and off when someone enters or leaves.

Control Solutions, Inc Although we are in the very early stages of analytics and machine learning when it comes to the edge, it is beginning to gain traction. I think James McHale, Managing Director at Memoori has said it best, “ It has long been clear that AI technology represents the future in building automation and beyond, but in the present, building performance software is helping humans improve automation while also nurturing its eventual successor – AI.”

Integrating analytics and machine learning at the edge level is becoming a prerequisite for today’s IoT-enabled buildings.               





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