AutomatedBuildings.com Interview

How Building Managers can Visualize Big Data

Big Data specifically means better ways to maintain equipment and more intelligent fault detection and prediction, or smarter ways to approach diagnostics as a whole.

Sinclair: What is “Big Data” as far as the building automation industry is concerned?

Turner: Big Data is kind of a buzz word that’s floating around a lot lately. When it’s used in the media, it’s typically referencing all the information bits that Internet giants like Google and Facebook collect every second. But it’s starting to stand for “business intelligence” on a broad scale, representing the ability to analyze mountains of computer-readable information and turn them into meaningful chunks that humans can understand, so that decision makers have the ability to make really informed choices about their business, whatever it may be.
For us in the building automation industry, Big Data specifically means better ways to maintain equipment and more intelligent fault detection and prediction, or smarter ways to approach diagnostics as a whole.

Turner: It starts out as tons of code that represents everything that building systems are doing at any given time. All of this information is filtering through Niagara as it runs the controls, but until now, there haven’t been too many ways to really make sense of that information. To solve this problem and really start playing with building data, we created DataEye Pro, which works on top of Niagara to create meaning out of all those data chunks.

While Niagara does a great job of normalizing data, this product goes one step further and models that data. For example, in the model, a rooftop air conditioning unit is a rooftop unit regardless of the manufacturer, communication protocol, or controller manufacturer; a lighting circuit is a lighting circuit regardless of the technology in the lighting fixture or lighting control panel. With this baseline understanding, the information in the database is modeled in a way that is exponentially more useful, because a standardized meaning is attached to the information bits.

Sinclair: Why is it important that the program access historic data if it is meant to be giving real-time information?

Turner: Well, in order to know if a system is working properly, we must understand how it normally works under the current conditions. This means the data engine must have some historical perspective to compare against the real-time values. As an extension of the NiagaraAX Framework, DataEye Pro accesses the Niagara history database for each of the data points in the model and then executes against the data model to make smart decisions. For example, with a heating system, the historic data shows what usage rates were on previous days with similar weather conditions. To determine an appropriate heating level for today, the data model would examine that historic data and compare that to weather information for this day and come up with a reasonable figure. All of this is then displayed graphically.

Turner: Charts and graphs, for the most part. It has an HTML5 interface and we have a whole User Experience team that develops really state-of-the-art graphics to visually interpret the data. The goal is to take all of the code and turn it into something that building managers can glance at and fully understand. This is also important when it comes to managers who are responsible for a portfolio of buildings. The interface needs to look the same for every building, so that time isn’t lost learning a new platform at every stop. This works because the data model is scalable, so it can be applied to an almost infinite number of buildings, delivering consistent results every time. And it can be run on the cloud, whether it is hosted by a data center in New York or on a virtual server in the corporate data center.

Turner: The data model also facilitates fault detection. So, once information is gathered, DataEye Pro can trigger an alarm, set off an additional formula, annunciate a graphic, email a building engineer, send an SMS text message, or execute other logic built in NiagaraAX.

The beauty is that Big Data and smart data models really make it possible to analyze, monitor and control any piece of an automated building system.

The beauty is that Big Data and smart data models really make it possible to analyze, monitor and control any piece of an automated building system.

[an error occurred while processing this directive]Sinclair: What would you say to Big Data skeptics or people who aren’t ready to make such a big shift in the way they operate their systems?

Turner: We all know that commercial and industrial buildings eat up a substantial amount of the United States’ overall energy consumption. It’s also fair to say that the mechanical and lighting control systems operating in these buildings generally operate less efficiently than modern systems make possible. These are two truths we kind of just accept in the industry. But it doesn’t have to be like that. There are really intuitive solutions available that are cost effective and open up so many possibilities for automated building systems and the people who manage them. It’s no longer a question of if Big Data will hit our industry, but when. Implementing a system like DataEye Pro at this point definitely puts buildings a bit ahead of their time, but the speed of innovation keeps getting faster, so it’s getting harder to justify waiting it out.

Brian Turner, LEED-AP BD&C, is President of Controlco, a leading-edge building automation solution provider and enterprise system integration firm. He provides hands-on expertise to architects, engineers and building owners to design and implement integrated building systems.

Joining the Oakland, California-based company in 1996 as part of the Control Systems Sales team, Turner has sold and supported the industry’s highest quality control systems for commercial and industrial buildings around the world. He became Vice President of the Professional Services division of Controlco in 2006 after showing leadership in developing a technical support network to promote contractor capabilities and user awareness.

Today, Turner leads a team of engineers and user experience designers in developing a new SaaS solution that will open up building data for energy managers to optimize their control systems, utilizing the most advanced data modeling, fault detection and prediction technologies currently available in the industry. As an internationally recognized expert in the field, Turner has helped professionals in the building industry optimize their controls and make their processes more efficient. He has participated in product studies for manufacturers and has made presentations at industry meetings and events to international audiences including building owners, distributors, manufacturers and system integrators. Turner earned his BS degree in Human Factors Psychology from California State University, East Bay, and later completed his MBA with an emphasis in Technology Management from the University of Phoenix.

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