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Architecture historians divide the evolution of buildings into different periods: Neo-classicism has its Greek columns, Art Deco has its glittering chrome, Brutalism has its swaths of concrete.
The architectural period we’re now entering is different. It’s not about how the doors look. It’s about who, or what, opens those doors. And, more importantly, it’s about what is going on behind those doors. How are occupants using the space? Are they comfortable? Are we creating healthy environments?
The answer to those questions lies in data. Lots and lots of data. And to make better sense of the gigabits of data these buildings are creating, we’re now able to use powerful analytics. These workspace analytics, along with the advances in automated fault detection, are the next big thing in smart buildings.
A Recent History of Smart Buildings
To understand why this is such a big deal, it’s worth exploring the origins of smart buildings. In my 25 years in the buildings industry, I’ve watched buildings grow ever-smarter.
Until the 1980s, building controls largely consisted of pneumatic controls: compressed air systems with thermostats that controlled valves, actuators, and other devices. The systems were effective yet inefficient — the only trend data available was manual chart recording. When something went wrong, you found about it through on-site manual inspection after an occupant complaint about comfort.
If the pneumatic era was like the Dark Ages, the 1980s until the mid-2010s were the Renaissance. Simple computers and direct digital control were introduced into the system. These computers sent signals to the controllers that regulated HVAC, lights, and controlled access. In addition to basic actions like setting temperatures, the system could also identify hotspots and manage zones in a more granular way. These systems allowed operators to better schedule equipment and start to trend building performance.
That was the standard for over 25 years. Today, I would argue buildings are entering the Enlightenment. It’s becoming commonplace to infuse digital IP communications throughout every layer of the system, from the centralized computers down to individual devices throughout the building. Advances in technology are driving down the cost of sensing devices dramatically, and the IP communication layer enables better interoperability, speed, and bandwidth.
An IP-based system also allows for much more data to flow between people and buildings. In the past, building operators would only monitor temperature where they had a control device. Now, buildings can host thousands of sensors monitoring temperature, indoor air quality, space occupancy, lighting levels, and life safety systems. The IP communication layer integrates all your data and connects that intelligence with your other buildings, wherever they are located. With this newfound visibility, you can track each of these systems in real-time, from a single pane of glass. Pretty enlightening stuff.
The Only Good Data is Actionable Data
The big question building operators now face is this: What should I do with all of this data? After all, the more noise you create, the harder it is to locate the signal. It’s like trying to find the needle in an ever-expanding haystack.
So, it’s not about data, it’s about better data analysis. It’s about monitoring your systems real time, employing building automation, and using powerful analytics. These analytics can sift through reams of data to identify patterns in usage, malfunctioning equipment, and discover actionable intelligence. In short, these approaches allow you to spot the needle in a fraction of a second, as opposed to discovering an issue during your next quarterly maintenance check.
What does this look like in real-world terms? In one case, at a university, a leaky valve was causing the chiller system to start during the winter months, working overtime to cool the air in the HVAC unit that was then reheated in the space. In other words, the HVAC system was fighting itself. And yet, the room temperature was kept within normal range, so neither the building management system nor the occupant could detect the anomaly.
Once the university added analytics and automated fault detection, the system identified this single leaky valve, and found it was costing them thousands of dollars a month in energy costs. A mechanic made the simple fix of re-connecting the control to the valve, and the problem was solved.
Digitized building analytics can identify all kinds of these performance gains. And not only that, it can rank them by dollar value, allowing building operators to do the most important work first.
Tackling 3 Challenges in Building Operations
Building operators, the people who use these tools, are facing challenges on a few fronts. With a comprehensive smart building approach involving cloud analytics, software controls at the edge device level, and an array of smart devices, building operators can now tackle their biggest challenges.
The first challenge is setting the right priorities. Actionable data and smart devices help building operators answer the “why” and “when” of dozens of complex questions every day. Just as two brains are better than one brain, dozens of petabytes of analyzed building data are also better than one brain. Questions such as, “What should I do first, repair a stuck damper or fix a failed compressor?” or “When should I do preventive maintenance?” no longer need to be answered through guesswork or lengthy calculations. The answers can be found quickly in the cloud.
A second, and related, challenge is staffing. In the past, a single facilities team served a single building. Now, companies are shifting to a single person running several buildings. There are fewer people to tackle more work. But with better intelligence into what exactly needs to be done and when, a single person can do much more.
Not only are budgets shrinking, there’s also a generational change unfolding in facilities departments. A Mach Energy report found that the average age of facilities managers was 51 years old, which suggests a looming talent shortfall in the coming years. As long-time building operators retire, so too does their institutional knowledge. To fill the gap, we’ll need more than occupational training. We’ll need the tools and A.I. that run our buildings and do a lot of the heavy lifting. Fortunately, the incoming generations are tech-savvy and will be able to embrace these digital approaches.
The third challenge is the confluence of megatrends that put will push buildings to do more with less. Both urbanization and expanding occupant demands around IoT are pushing building operators to accommodate greater density and connectivity. At the same time, operators need to meet these growing demands with less energy. Globally, buildings account for 39 percent of global greenhouse gas emissions and possess a massive untapped potential for energy efficiency. Digitization in buildings can cut 10 percent of total energy use in residential and commercial buildings by 2040, which would make a significant dent in global emissions.
A Step Change for Smart Buildings
Buildings have been growing smarter for years. But buildings fitted with IP-based connectivity down to the device level represents a step change in smart buildings, one that is just beginning today. This approach exponentially increases the amount of data flowing through a building. And with a great amount of data comes great responsibility: It is now necessary to introduce building automation analytics that make sense of all the 1s and 0s. When we introduce this powerful intelligence into the equation, it becomes possible to achieve greater occupant comfort in the face of smaller staff, shrinking budgets, and expanding sustainability goals. That’s what this is all about: doing more while using less of our facility and our planet’s resources.
Chris Collins is Vice President of Digital Energy, Schneider Electric