How Machine Learning can Transform Facilities Management

New technology is behind the radical changes constantly taking place within the facilities management profession.

In particular, facilities managers are fast waking up to the opportunities presented by artificial intelligence and machine learning, which have significant implications for the way they manage buildings.

What is machine learning, and how does it work?

Machine learning is all about teaching computers to think for themselves. It teaches computers to comb through data gathered from various smart systems to make decisions based on the patterns it detects. It can do this based on an existing algorithm, or work entirely independently.

For facilities management – and smart buildings in particular – this has huge consequences. For instance, a machine learning system could be developed to predict when replacement parts are needed for a piece of equipment, based on measurable factors like urgency, cost and budget.

As a result, equipment can monitor itself, alerting facilities managers to abnormalities before they arise; it can even learn how to perform actions on its own – such as ordering replacement parts or cleaning out filters – based on knowledge and data gained from facilities managers. For instance, if an FM runs a process to clean out a filter following a clog, the computer can repeat that action automatically the next time it detects that particular fault.

Reducing inefficiencies

Machine learning therefore makes running certain processes within buildings much more efficient. This has particular relevance for energy management – and with sustainability and energy efficiency becoming such key issues, facilities managers will start to take notice of the opportunities of machine learning.

For instance, machine learning can measure daily footfall in a building over the course of a week, and automatically adjust heating, lighting, security systems and so on according to patterns it has detected. It can even take into account public holidays when footfall is lower, and times of the year – such as Christmas or during the summer holidays – when fewer people tend to be in work.

In the future, machine learning could also let computers draw conclusions from, for instance, meeting schedules, heating meeting rooms to a preferred temperature before meetings take place, rather than inefficiently doing so during the meeting.

Smarter data storage

A final advantage is smart data storage. Smart buildings can produce an enormous amount of data, which in turn requires a reliable storage system that reduces the risks posed by human involvement. Computers can store, manage and analyse massive amounts of data at a speed and level of accuracy simply unattainable by humans and, better still, it can categorise data based on the kind of action it requires. This can then help the facilities manager organised their workload and work out how to use the data effectively – it’s relatively simple, but given the reliance smart buildings technology has on data, incredibly critical.

Combined with predictive analytics, machine learning can provide facilities managers with insights and data to improve their own decision-making. With all the information they need properly analysed and categorised, FMs will be better able to optimise their job performance. This reduces costs and produces the best results.

To learn more about the technologies transforming facilities management, including machine learning and artificial intelligence, sign up for your free ticket to Facilities Show 2019 at ExCeL London on 18-20 June, and access presentations, seminars and product demonstrations of the most innovative technologies on the market.