Ken Sinclair’s Automated Buildings July Theme — Performance Software Evolving with Self Machine Learning

Ken_Sinclair_Photo Ken Sinclair, owner and editor of Automated Buildings, is a great gatherer of information. It takes a lot of energy and perspicacity to rally an epic monthly battle cry for our industry and continuously call forth such an exceptional litany of industry experts. Ken judiciously sorts out for us, the IoT wheat from the IoT chaff, and then translates the fast and esoteric talk of our trade into slower more comprehensive reflections that generously reward the reading time invested. This July edition is no exception. Fresh off the trails of Silicon Valley, Ken captures the spirit of innovation from the 2016 Realcomm/IBcon show and gives us much deeper insight into performance software, machine learning, and portends the coming of our digital savior (perhaps) — Artificial Intelligence.

My favorite extractions from Ken’s editorial:

“Summary: With software that leverages tagging and data modeling, we are beginning to greatly reduce the number of mouse clicks required to implement a solution. Following Muench’s Corollary to Metcalfe’s Law, this streamlining of the user experience is unlocking the true value of a connected system. Participation in Project Haystack is giving property managers, building owners and system integrators a big head start in the establishment of an in-house point taxonomy. They can then enforce vendor specifications that call for standardized tagging and data modeling across a portfolio and for all aspects of building operations. Project Haystack is supported by an active and growing open-source community of developers who are collaborating on improving its definitions and modeling methodology. For all these reasons, it is the most future-proof approach to monetizing your building data.”

Infusing Machine Learning with Artificial Intelligence As anyone who endures a call with an automated customer “help line” quickly learns, robots have a frustrating inability to understand sarcasm. – Sophie Loire, Ph.D., Research and Technology Fellow, Chris Tagge, Ph.D., CEO, Igor Mezic, Ph.D., Chief Scientific and Technical Advisor, Co-Founder, Ecorithm, Inc:

“Software combines several key elements of artificial intelligence with machine learning to rapidly and automatically identify and classify building data with exceptional accuracy. Similar to the metadata embedded in the communication example described above, each time series of building data and its underlying dynamic can be completely described by a set of triplets corresponding to its magnitude (similar to volume, this is the height of the oscillation), period (similar to pitch, this is the time scale of the oscillation), and phase (similar to timing, this is the starting point alignment of two time series of data with respect to a common time origin). The result is called the spectral pattern, which provides an automatically measurable and classifiable signature of behavior.”

List of July, 2016 Articles:

Infusing Machine Learning with Artificial Intelligence, Sophie Loire, Chris Tagge, Igor Mezic, Ecorithm, Inc.

The Strategy and Payoffs of Meta-Data Tagging, B. Scott Muench, J2 Innovations

Edge-Analytics Sensors For Smart Buildings, Itamar Roth, PointGrab

What’s more important – The Device or the Cloud? Greg Barnes, Activelogix LLC

Plugged In, Kevin Callahan and Kevin Clinger, Alerton

New Investments in Green Technologies, Karina Wright, Reliable Controls

Grundfos Living Lab, Sven Goldstein, Beckhoff Automation GmbH & Co. KG

It’s On!! Haystack Connect 2017, John Petze, SkyFoundry & Marc Petock, Lynxspring, Inc.
To Upgrade, Or Not Building Automation, Brandon Baisas, ASSET Technologies, LLC.
Smart Bldgs Can Be ‘The Nodes’ Of The Smart Grid, James McHale, Memoori

Should Your Plant Have an Energy Audit? Bill Holmes, Holmes AutoPilot LLC

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