The next largely unchartered territory for the property sector is that of Machine Learning and Artificial Intelligence.
Until now, buildings have not produced sufficient data to allow any data science to be of value. However, with IoT devices and connected digital twins, the opportunity is a reality.
As the property sector data lakes grow over the years ahead, we will be able to learn from patterns in how we use buildings and how they perform. With this information, we can predict how spaces are used and how we can optimise their performance.
For example, we will be able to carry out predictive maintenance or reduce energy costs based on anticipated space utilisation.
The artificial intelligence develops as the data grows and patterns emerge:
1. See – updating and learning
2. Think – reasoning and optimising
3. Do – informing and acting
Within buildings this learning provides an increasing level of value:
An advance warning of a system failure (not a warning when it has failed).
A prediction of how a system is going to operate and when parts need to be replaced.
Using performance data to maximise life-cycle value and utilisation of resources.
The concept of Machine Learning and Artificial Intelligence is becoming increasingly common for consumers. For example, Tesla cars are continually gathering data that they learn from. The self-driving mode for example predicts where a road accident may occur, or a child running on the road.
In buildings, scanners at the entrance to buildings are calculating how many people are entering it by analysing shapes rather than using cameras that have privacy issues.
Buildings already provide huge amounts of data which is not captured. For example, the access control system provides user information, the room booking systems identifies space utilisation whilst the CCTV can track people’s movement.
We are very much at the start of this journey in property, however, the amount of information we are collecting is growing. Data scientists are beginning to become interested in how buildings operate and academics are starting to interrogate the data.
Much of the current thinking is at a single building level, however as more buildings become connected the data will grow. Connected buildings can then integrate with the smart city taking optimisation to the next level.
In the UK, the government is developing a national digital twin which is establishing standards so that information can be collected consistently over the next 30 years.
In an industry where we are still laying bricks and plastering walls, the reality of machine learning and artificial intelligence might seem a long way away. However, with the growth of data collection and digital twins, this may not be the case.
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