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AHR 2015 Session: Smart Buildings, IoT, and Smart Cities
January 5, 2015 - Building Automation
by Ken Sinclair
The third session at AHRExpo 2015 in Chicago focuses on the connection between smart buildings, the Internet of Things, and smart cities.
3. Jan. 27, 9:00 am, at AHRExpo 2015 Chicago: “How Smart Automated Buildings and IoT create Smart Cities.”
To provide connections and information about IoT known interactions that will alter our journey. Increased urbanization also means a greater number of buildings and key urban systems. There appears to be an overarching commonality in smart buildings and smart cities; it is the use of advanced technology to improve the “performance” of the entity. It involves automation, information technology, communications, integration, data mining, and analytics. Jim Sinopoli, Brad White, and Ken Sinclair will discuss creating Smart Cities.
The following article will provide some insight into this session:
“The Road to the Smart City.” A starting point in transforming a city to a smart city is to look inward. - Jim Sinopoli PE, LEED BD+C, RCCD Managing Principal, Smart Buildings LLC
I’ll leave you with some thoughts from the article, “Learning from People.” By using input from humans, we can greatly improve the systems, and therefore buildings, that serve our occupants. - David Weidberg, Client Solutions Manager, Building Robotics.
The time is now! With machine learning at your doorstep, what do we do - run, hide or embrace? No, I am not talking about the Terminator, but I am talking about your existing building having the capacity to evolve and learn from the surplus of data that already exists in your facility and within your occupants.
While the concept might sound new, in the book How Buildings Learn, Stewart Brand professed the philosophy of ever-adapting buildings long before machine-learning technology existed for buildings. As he writes, “First we shape our buildings, then, they shape us, then we shape them again – ad infinitum.” He is describing the notion that buildings are not static, but that they are dynamic and continually changing based on occupants, technology and environment. Machine learning can play a vital role in enabling buildings to adjust to peoples’ needs, thus helping shape the buildings in which we work.
To the average person, the concept of machine learning is only foreign by name. We interact with machine learning on a daily basis. For example, Amazon, Netflix, Google, and countless other companies use machine learning to personalize your experience on their websites and provide predictive insight into products that you might like based upon your previous inputs. These companies have invested heavily in machine learning because people respond to curated content in the form of loyalty or purchases. The reason people use these services is because they provide a tailored experience – one that provides more meaningful content and saves time from browsing through unwanted content.
Much like people’s experience on the internet, building occupants want meaningful personalization in their workspaces. The concept of changing temperature or lighting levels at work might seem trivial, but it is something we all control in other environments, including one’s home and car. For building managers, giving occupants this type of control has always been controversial due to energy concerns and the difficulty of managing different preferences among occupants. So, how can machine learning help?
Machine learning creates a perpetual learning environment by using various data streams from the building management system along with the use of human input.
Ken Sinclair is the founder, owner, and publisher of an online resource called AutomatedBuildings.com. He writes a monthly column for FacilitiesNet.com about what is new in the Internet of Things (IOT) for building automation.