🎧#31 From Data Swamps to Full Autonomous Buildings through an AI-driven “Middle-Out” Strategy - Troy Harvey

What are the challenges with designing and operating high performance buildings today? What is the quantum ontology and what does the future look like for Smarter Buildings everywhere?

  
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“You're just filling up these oceans of data and then you're like, go, dang, what am I going to do with all this data? And then you hire a bunch of data scientists and, and they, they go dig around like miners, hoping they might find some value.” -Troy Harvey

From an electrical engineer to designing products for a wide variety of industries to the grandfather of quantum buildings and co-founder of Passive Logic. In this episode, we get to hear the origin story of one of the most interesting companies in the smart building/energy space when we talk to Troy Harvey.

Some listeners might remember Troy Harvey (not McClure) from inspirational sessions and articles, such as:

Obstacles and Opportunities for HVACR in the Next Decade, moderated by Nicolas Waern.

And of course, the phenomenal article series around quantum ontologies and self-driving buildings at www.automatedbuildings.com.

These are some of the questions that are being answered in the episode!

  • When will Passive Logic hit the market?

  • Is Passive Logic a Cloud, Edge hybrid platform?

  • What are the most important KPIs that stand out in relation to existing solutions in the building automation market?

  • Why do need we to invite people to the industry to solve the hardest problems?

  • Is the greener pasture on the other side?

  • Why is it so challenging with integration?

  • What is the relationship between systems complexity and computer science?

  • What is the quantum standard?

  • What’s the BIG missing piece with ontologies today?

  • How well does Passive Logic play with others?

  • How can companies build their Digital Twins?

  • What does it mean with Generative Autonomous Platforms?

  • How unique is the offering from Passive Logic?

  • How do you make Ph.D.-level knowledge accessible and understandable for the average installer in a scalable way?

  • Why and where is open-source lagging?

  • What are the places of innovation that don’t fall into the open-source category?

  • What is the relationship between Deep Digital Twins and AI?

  • Some of our favorite bold statements from Troy was:

“You'll be able to get in and out from, from design, uh, you know, deploy wire commission about 10 times faster than you will with conventional platforms.”

“If you look at Microsoft's notion of digital twins, well, it's like a programming language in the web. It defines what a flow, isn’t an image like, you know,  these are very low level concepts and arguably not useful or interesting”


The thing is that companies today are data-rich, but information poor. We live in the data dark ages, desperately trying to get to the information renAIssance. And when You have a lot of labeled information, what do you do with that? Is it possible to let people work within their silo, where the data is part of a larger context with information that will stay with the building over time? Do you agree or disagree?

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