Paul Deverell: Artificial Intelligence leads to transparency

Published: 20. 04. 2021

Is AI something property professionals should be aware of because it’s the future? Or because if they’re not implementing it today in buildings, they’re already falling behind?

Definitely it’s something professionals should be aware of and I think many people are. With regards to falling behind, I don’t think that applies only to AI but to building technologies in general.

If we are paying specific attention to building management related AI driven software tools that are currently springing up, we need to be aware that they are not able to function as stand-alone solutions or as complete replacements for building management systems (BMS). They still need to be connected to an existing framework in order to gather data. It’s important to check the current set up of the building to determine whether or not an additional AI or analytics layer could be implemented in future and if it could bring any benefits.

BMS, IoT, energy management and AI are often misunderstood as being separate when in reality the opposite is true. Today these functions are mostly software that sit in the cloud and can be accessed from a single platform. It works in a similar way to your smart phone: You buy a hardware unit and then access or connect to these tools via the internet. The advent of  Software as a Service (SaaS) platforms means building owners don’t need to pay large upfront fees and can often access these features or make changes (at a low cost) whenever they choose.

What are the current applications for AI in commercial real estate that owners should be considering? Does it make sense for developers of individual buildings to be planning buildings with AI in mind?
There are already many AI-based tools being implemented in real estate. But here we are focusing on the building technologies themselves. As previously mentioned, an AI layer in this context is a software tool that can augment the monitoring and management of core building systems. AI for buildings is still in its early stages and therefore we wouldn’t recommend to fully hand over the management of buildings to AI just yet. However, we have been studying this in detail and in terms of monitoring the HVAC system we can definitely say it can provide benefits.

A modern BMS set up has a lot of built in “intelligence” capabilities (such as weather systems monitoring, preventative maintenance etc.). But an additional AI layer can augment the performance of the building even further. Unlike humans, AI can monitor thousands, even millions of data sets, 24 hours per day. The advantage being AI’s ability to learn from pattern recognition, something many BMS systems or humans are not able to do at such scale. Therefore, we see applications in the form of AI augmenting building manager’s decision making methodology through providing deep insights and recommendations for HVAC and other equipment.

Additionally, because AI can recognise patterns, it can also track the performance degradation of critical equipment and infrastructure over time and inform managers (prior to any failures) that it may be time for servicing or replacement.

We recommend to implement AI initially on a trial basis as an advanced data gathering and analytics tool that provides recommendations to building managers. Then monitor the improvement in building performance and reductions in energy use, maintenance costs and building downtime benchmarked against “before installation” figures. The proof is in the pudding, as we say.

What types of data should all new buildings be collecting in order to be competitive in future?
Energy is of course a major talking point. The more accurate a building and its managers can monitor and adjust the performance of equipment the better it will perform. Often equipment may be running at night or during weekends without the owner’s or occupier’s knowledge. AI can provide a valuable way to capture data and spot such anomalies. Energy data can also serve as a basis for optimising the structure of energy supply contracts by accurately predicting reserve energy requirements.

As a general rule we can say that occupier space (in mixed use or office buildings) accounts for approximately 60-70% of a building’s total energy consumption, and up to 100% for industrial. Occupiers are demanding transparent data from buildings to determine where they can make operational improvements and to benchmark building performance.

And while you’d expect a newly commissioned building to automatically perform perfectly, however, this is not always the case. In fact, tracking the data over the first 2-3 years of a new building’s life can be where the most improvements are to be garnered. Over the longer-term the data can be used to make sure building managers are making adjustments that continue maintaining those improvements.

According to the recent REHVA Quality Management For Buildings Report, “Studies of newly commissioned buildings worldwide have shown the gap between design intent and operational energy consumption to be as large as 30% or more.” The report found that studies in Germany identified saving potentials of 15% in condensing boilers and up to 30% in air handling systems where energy consumption could actually be avoided through low or no investment cost.

Building owners are sometimes not aware of the advantages of having control over their data, where it is stored and how to make use of it. One important example is in the case where a building owner or manager has outsourced the facility management to a 3rd party provider. Often providers will use their own internal software for logging and managing repairs and revisions to building equipment. This valuable data should be comprehensively managed by owners for service monitoring, checking activities performed against BMS data and ensuring the information isn’t lost should there be a change of FM service provider.

It’s hard to overstate how important data are: From building users that want to see air quality on a dashboard or smart phone, to capital markets, banks and governments, the gathering of “building-direct” data is becoming a necessity.

How difficult is it to retrofit buildings and is it worth it?
Performing a technology inspection (what we call a “health-check”) will determine where real improvements can be made. This should take into account critical equipment, hardware and software systems. Each building is very different. Some may benefit greatly from retrofitting whilst with others it may be more complex. A post-inspection report should highlight areas where there is an urgent need to make changes; conversely outline points of lower priority that can be gradually updated over time. Furthermore, building owners should take into account the availability of government grants for energy retrofitting projects as this can contribute to overall feasibility and shorten the return on investment period.

Regarding technology retrofits in general; in some cases it is a necessity. There comes a time in every building’s life when a comprehensive review of the building systems (HVAC, BMS etc.) will need to be performed. This is usually around the 13-15 year mark, depending on how well the building was maintained. We often see building owners and managers making mistakes by ignoring this fact and replacing components once they fail or begin running poorly without a plan in place. This is almost always a waste of money as it’s necessary to take a look at why such components failed and the implications of replacement in the bigger context of the building systems. We are often involved in projects where owners have spent money on replacements only to have to spend more in future due to a lack of planning.

What’s the future of AI in real estate?
Over time (and with the necessary improvement in data quality) AI and machine learning will gradually take over the management of buildings. However, for the time being AI tools will be used to help building managers adjust the performance of key infrastructure and track anomalies with greater accuracy and insight.

What do you see as the connection between AI and achieving and maintaining ESG?
ESG reporting is becoming more important than ever. Investors, employees and others are playing a key role in driving this trend. We expect AI tools to play a role along the information chain in future, especially for investment firms, banks and capital markets players. Currently, there is still a lot of manual input along the ESG data collection chain. In future we expect this to be automated, ensuring the data are accurate and have not been manipulated in any way. In this context, the ability to easily connect buildings directly to ESG tools will play a role; with less manual input required along the data chain.

 

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