Pete Segall
Pete Segall
ATS Automation
Pete leads a team of energy and building performance engineers with the core mission of better building performance through optimizing energy management systems, developing new and innovative facility solutions, and leveraging state grants and utility incentives. Pete has been providing energy management and facility solutions consulting support across all vertical markets for over 23 years. Pete has a mechanical engineering degree from the University of Washington, an executive leadership certificate from Seattle University, and is a Certified Energy and Demand Side Manager. Beyond efficiency, Pete’s passion is animal welfare and is on the board of directors for the Seattle Humane Society and volunteers weekly providing dog adoption support.
All Sessions by Pete Segall
Data in Context
Almost all buildings have the capability to generate volumes of operational data and many also deploy fault detection technology to alert operators of problems. Unfortunately, too often there isn’t sufficient context for that fault to properly diagnosis causation or what solutions to deploy to fix it. This condition can be particularly problematic for building owners and managers that don’t have the in-house expertise often found at enterprise scale entities. For these managers, the challenge is to find the right resources to put their operational data into context and do so affordably. This session will explore examples of how to put affordable solutions in place to properly put data in context.
Data Analytics – Making Smart Actionable
Building data becomes actionable when good analytics are applied and made useful to facility managers/operators. This session will have two case study presentations which demonstrate this followed by a larger SME moderated panel.
Artificial Intelligence/Machine Learning in Buildings: The Future is Already Here
Artificial intelligence (AI) and machine learning (ML) are embedding themselves in almost all aspects of our lives -building operations included. Building systems, especially HVAC, are a complicated set of interrelated components reacting to an almost endless stream of dynamic variables, be it weather, occupancy, or space utilization. Historically, it has been a challenge, to say the least, for building operations to optimize system performance in such a dynamic condition. The use of AI/ML is now proving itself as capable of analyzing and acting on this information to drive better building performance. This session will bring together pioneers in this field as well as real building experience in the deployment of AI/ML in the commercial building space.