The AI Version of Me
I don’t necessarily like to write about concepts that are not applicable today. Especially in the facility management industry, where innovative ideas tend to crawl for 10 years, then walk for 10, then finally get to running (mainstream adoption) after that. But I can’t help myself with AI for smart buildings because in a sentence:
I want a computer to replace me at my job.
That’s no exaggeration. Let’s start with what I do. I find ways to make buildings more comfortable, energy efficient, and run with less downtime.
That will all be done by AI in the future, and one day I hope to help advance the cause. Why? Because there is not enough time, money, or duplicates of myself to be constantly evaluating and identifying all the opportunities that exist 24/7/365 to make buildings run better. The most time I get in a typical building that I work in is a few months.
I use a combination of gathering time-series equipment operating data, on-site testing, and engineering judgement/calculations to understand how a building functions. I find everything that’s not working or could work better and come up with a detailed plan to make the fixes necessary to achieve the goals of the project. How could a computer do that? Well, the first stage is already being done.
Most of the analysis in my field of work is done in excel spreadsheets. Time-series data is exported from the building control systems, and poured over to look for insights.
The facilities operations industry has only recently begun to adopt analytic software to automatically sift through the massive amounts of data produced by buildings.
A lot of this manual analysis can be codified into “rules”, “functions”, or “algorithms” within these softwares to find the things that are important (too much energy use, broken equipment, etc). This is definitely the first step to better operating buildings, but it’s not a seismic shift. It is another tool in the toolbox of building operators to do their job more effectively.
If analytics is the logical next step from where we are today, machine learning and AI would be the gigantic leap right after.
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