Making smart buildings smarter with artificial intelligence 

By: Tom Rule, Segment Head, Digital Buildings, Siemens Smart Infrastructure USA 

What is artificial intelligence (AI)?

Artificial intelligence is the ability for computers to learn things that they were not explicitly taught. Of course, by “taught,” we mean programmed. AI is the result of machine learning. Artificial intelligence and machine learning are related but not synonymous.

 

How machines learn is similar to how people learn. Machines, like us, are given several examples of end results. They are then either told what kind of result each example is or asked to observe similarities in the results. A human learns that a hard item at high speeds against one’s hand is painful. A machine learns that certain characteristics typically denote a spam email. From here, both learners can predict the outcome of a future example.

 

How can smart buildings use AI?

The goal of any smart building is to make everything better.

  • Better energy management reduces costs and carbon emissions, helping organizations achieve cost and sustainability goals.
  • Better comfort management creates more enjoyable working environments, improving occupant health and well-being.
  • Better systems optimization results in better uptime and productivity for systems and people alike.

 

The key to making smart buildings better is using data in the right way. Smart buildings create tons of data. Every second, temperatures, pressures, on/off statuses, and more come rolling into the system. The problem is that data is a rich ore, not a finished product. A person cannot sift through all that data by oneself. It takes machines to go through such amounts of data, and this is where artificial intelligence starts to shine.

 

AI thrives on data. In fact, large amounts of data are critical for AI to work properly, so the more the better. What machines can do that people cannot is process that data quickly enough to get results in a timely manner.

Examples of AI in buildings

Rhetoric about artificial intelligence sometimes can seem academic or ethereal, so let us look at three examples of how AI can make a big difference.

 

  1. You have a room at the perfect temperature and there are no complaints. However, your AI platform recognizes that both your hot-water and cold-water flow are fairly high, so there’s evidently a problem. What seemed to be a working situation turned out to be a waste of energy. It would be unlikely that a human would discover this, but with AI continuously analyzing data, it automatically determined that this was a problem. How it learned this was that other similar rooms did not require such competing water flow, so it could recognize this as an anomaly. The platform can either display an alert or generate a work order to have maintenance examine the issue further.
  2. After a lengthy period of collecting data, AI sees a valve that is behaving the same as other valves do when they are about to fail. It could be because the valve is slow to move or some other data point that was of little interest previously. Before building management even knows there is a problem, AI can order a spare valve from the supplier and schedule its replacement. This is a leap forward in fault detection and diagnostics that are proactive and works toward eliminating unexpected downtime.
  3. Finally, let us look at how occupancy can affect HVAC usage. With 40% of a building’s energy use in HVAC, this is a major focus. Many buildings have already installed occupancy sensors to avoid spending energy on empty spaces, but analytics can take that further. With a standard occupancy sensor, lights, shades, and temperature kick in if someone enters a room. However, AI has determined that a few people have triggered a wide array of zones when only a few could have sufficed. It could be that the organization does not need as many meeting rooms, or maybe they need more but smaller. The goal is to achieve more utilization of fewer resources.

How Siemens is using AI to help customers

The smart building is a continually growing and evolving sector of technologies. Siemens keeps up with these changes by continually developing transformative solutions for customers that are effective and valuable.

 

Siemens has developed a new cloud-based, AI-enabled platform for smart buildings that brings building insights to managers, owners, and leaders that they have never seen before. It is called Building X, and it’s a new way of getting the most out of smart buildings. Part of the Xcelerator business platform, Building X breaks data silos and makes use of data that allows organizations to achieve their goals of sustainability, productivity, and well-being. The artificial intelligence, developed by Siemens itself through years of experience, is a new way of using data to analyze systems like never before. Leap into the future of smart buildings.

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