Data Innovators Azizan Aziz (center) with his team at Carnegie Mellon's Intelligent Workplace

Published on September 20th, 2013 | by Travis Korte

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4 Questions for Green Building Sensor Expert Azizan Aziz

The Center for Data Innovation spoke with Azizan Aziz, a Senior Research Architect in Carnegie Mellon University’s architecture department, about a project that uses sensor data to encourage environmentally friendly practices among office workers. Much of Aziz’s work takes place in the Intelligent Workplace, a sensor-enriched office environment where researchers study energy efficiency and occupant experience using themselves as the test subjects.

This interview has been edited for content and clarity.

Travis Korte: Can you give me a brief overview of the Intelligent Workplace?

Azizan Aziz: The Intelligent Workplace is a 75,000 square foot facility, built in 1997. We call it a living lab. We do lots and lots of experiments and demonstrations for visitors, practicing professionals, other academics and students. It also is a teaching facility, and it houses the faculty and also the graduate students for the Center for Building Performance and Diagnostics, which is part of the school of architecture. We do a lot of tests on ourselves; a lot of the pilot prototyping is done in the lab before we deploy it somewhere else.

TK: And what specific projects are you working on?

AA: One of the things I work on is called Empowering Occupants Toward Sustainable Practices. The purpose is to give occupants information about the energy use inside a building, and encourage them to control the equipment and turn things on and off. This project is funded by the Department of Energy under a big umbrella project called the Energy Efficient Building (EEB) Hub. There are multiple projects within the EEB hub umbrella, focusing on tool development, looking at high performance enclosure systems, better windows, better control strategies, data warehouse solutions all the way to workforce training and policy and market behavior. This is one of the projects CMU is engaged in—how can we engage the occupants in an office setting toward environmental behavior. Unlike in a home, where if you don’t save energy you have to pay for it, in an office setting there’s usually no consequences.

From the CMU perspective, what we believe in is that given information about your office environment and specific feedback to your own energy consumption, people will be able to save energy. In every office, you have your mechanical systems to heat and cool your buildings, you have your lighting systems, and the other energy component is the plug load management. What we’ve been focusing on is this plug load management. We’ve developed a dashboard that shows the occupant hourly, daily, weekly and monthly energy consumption, and based on the pattern of consumption we give a recommendation of when to turn things on and off. We can also tell them whether some of the appliances are outdated, can we replace them toward Energy Star-rated appliances to lower energy consumption, for example? We hope that this will expand beyond plug load to other things like turning off the lighting when there’s a lot more daylight—which is what we’re developing right now—a dashboard for lighting and a dashboard for mechanical systems.

TK: What do you see in the future for the project?

AA: Currently the [sensor] hardware is plug-based and we’ve developed the interface on top of that. But we believe in an integrated system; when you look holistically in a building there is of course power consumption, but we want to reduce power consumption while increasing occupant comfort, satisfaction and performance. To do that, occupant comfort is not just about energy consumption; it’s also about air quality, cooling and heating, and acoustic quality. These have an energy component to them, and in the current building automation system environment, different companies make the various systems using various communication protocols. So we’re using [a special server] to put all the various data in an aggregated format in very simple to understand form.

Also, we’re talking to the local Pittsburgh chapter of the U.S. Green Building Alliance, and proposing to collect their data in real-time as [granularly] as possible, and then use the server infrastructure to get all the data together and show comparisons, make recommendations and optimizations. They don’t have the data, but how can we create policy when we don’t have data? So we help with that. We’re trying to work with utility companies to get the data directly and also with the buildings themselves.

TK: What is it going to take for systems like these to be adopted? Will it require an overhaul of the thinking around how we build?

AA: You’re exactly right. The challenge in the nonresidential building sector is offices and school buildings. Within the office sector, the biggest chunk is the small offices, defined as anything below 50,000 ft2. Small buildings, “mom and pop” operations, may not even have a building automation system. There is a challenge to get that data and then make any kind of improvement. It’s not that we don’t care about the 10%, but to make an impact in energy conservation, the 90% is really the low hanging fruit.

On the other hand, we’re also making a proposal to the Department of Defense, trying to promote base-wide, installation-wide monitoring; then we can get the proper policy or protocol for that organization. The reason we’re focusing on the DOD is because we have a project with them for the Air Force base in Pittsburgh, and we found there that all the buildings have building automation systems. That’s just the armed forces for you. All the buildings have automated systems, but in a typical commercial building setting, 90% of that is small offices, and I suspect those don’t have building automation systems.

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About the Author

Travis Korte is a research analyst at the Center for Data Innovation specializing in data science applications and open data. He has a background in journalism, computer science and statistics. Prior to joining the Center for Data Innovation, he launched the Science vertical of The Huffington Post and served as its Associate Editor, covering a wide range of science and technology topics. He has worked on data science projects with HuffPost and other organizations. Before this, he graduated with highest honors from the University of California, Berkeley, having studied critical theory and completed coursework in computer science and economics. His research interests are in computational social science and using data to engage with complex social systems. You can follow him on Twitter @traviskorte.



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