Rise of the machines
The concept of artificial intelligence is nothing new, but it’s quickly coming into its own. MEGAN RAY NICHOLS brings the complicated world of digital disruption in facility management back to basics.
In the real world — not science fiction — artificial intelligence has become incredibly advanced and is being used to augment the way we interact with technology. Smart voice assistants like Siri or Alexa are transforming the average user experience at the simple command of your voice.
Machine learning, on the other hand, is an offshoot of AI, which essentially involves extracting insights from digital data. AI is an algorithmic platform that follows a loose script through to the end. But machine learning makes use of more cognitive forms of interactivity and mirrors the human mind. The best part is that machine learning platforms are designed to learn and improve over time as they ingest more data and have their own ‘experiences’.
Machine learning in building operations
When applied to building operations, machine learning has a lot to offer. As the industry becomes more reliant on digital content and information, these technologies will become more powerful. They’ll have more data to analyse and extract from, and that means more robust knowledge and much more reliable predictions.
Here are some of the ways the technology is influencing building operations:
1. Predictive building maintenance
Facility managers can now tap into reliable predictive maintenance tools and systems. Before, the process relied on a limited set of information, but it now incorporates a wider gamut of viewpoints. For example, maintenance calls can be made based on a system’s past performance, previous malfunctions, diminishing output and much more.
The system builds a forecast for both short- and long-term improvements. They can even be used to convert processes, hardware or systems into more efficient ones.
Another aspect of this application is that building owners can better understand how their facilities are being used. This allows them to tap into frequently underutilised areas and even convert them into something more practical for day-to-day operations.
2. More accurate occupant datasets
With the help of IoT and connected devices, building managers can gather more robust sets of information on occupancy and traffic. They might learn how people navigate a building’s space and what that means for energy usage. They might also learn about areas that are overcrowded and causing productivity issues.
This will be helpful in the retail and customer support sectors, as it ties into wayfinding and customer experience programs. Machine learning tools can help analyse all the incoming data to find areas for improvement and new opportunities.
Consider the average commercial restroom and their typical designs. At Brisbane Airport, an interactive touch screen system was installed to track direct user feedback. In a scenario like this, occupancy data, building maps and behavioural data can be analysed by a machine learning tool to come up with better bathroom designs, further improving user experience.
More efficient management of occupancy can lead to increased tenant retention, costs savings, higher customer and employee ratings.
3. More efficient use of resources
In building operations, energy is one of the most challenging resources to manage. The more people you have inside a facility, the higher the energy consumption. That goes hand-in-hand with any equipment, hardware or infrastructure you have switched on.
Even something like lighting can be leveraged more efficiently to save money and power. An automated system that turns lights off in a vacant room would save hundreds, if not thousands, of dollars a year.
Machine learning tools can help analyse all incoming information to find better and more reliable ways to use resources, including energy.
This is happening right now in most data centres. Alphabet — Google’s parent company — used its DeepMind machine learning platform to reduce energy costs within its data centres. With the help of DeepMind, Alphabet achieved a reduction of about 40 percent in cooling costs.
Creating the opportunity for machine learning
Machine learning offers incredible opportunities, particularly when it comes to the management of building operations and resource usage. From staffing and personnel management to automated lighting and even more efficient use of building space, there’s a lot that can be done with the technology to alleviate some of the more common building management stressors.
More importantly, this technology can help building managers become more knowledgeable and accurate than ever, and create rich properties rife with optimisation and convenience.
Megan Ray Nichols is a technical writer and blogger. Her work has been published on sites like Icons of Infrastructure, Industry Week, and Read Write. Keep up with Megan by subscribing to her easy to understand technology blog, Schooled By Science, to follow her discussions on engineering, technology and science.
Image: Olivier Collet © unsplash.com