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AI: Driving the Future of Smart Buildings

25 Jan 2024

Smart buildings pump out data.

Where there’s data, there’s opportunity for AI.

We’ve already seen AI drive change across multiple sectors. As AI driven optimisation continues, AI integrated smart buildings are set to become the benchmark.

Whilst a smart building can be thought of as a single entity, it is in fact a node of convergence for a network of systems and devices. These communicate to give a seamless tenant experience. It’s these interactions that provide the data that maps out a building’s efficiency. By capitalising on AI, smart buildings can optimise environments to drive sustainable practices.

Smart buildings: an evolutionary timeline

Smart building technology has delivered benefits across the built environment for quite some time. Probably quite a bit longer than many would imagine.

The concept of the smart building has actually been evolving over several decades. It developed gradually as innovations in various aspects of building automation and control have advanced.

1970s & 1980s: the early years

Even around the 70s and 80s, simple automated HVAC controls had their place. These were followed in the 1990s by the integration of more sophisticated control systems, incorporating things like lighting control and basic sensor networks.

Early 2000s: who came first RFID or IoT

In the 2000s, Radio Frequency Identification saw widespread uptake for things like inventory monitoring and simple access cards. Around the same time, storing data in the cloud was in its infancy, but making progress.

2010s: IoT to infinity

The 2010s are really when Internet of Things (IoT) gained mass appeal at the consumer level. Smart devices and smart building integrations expanded rapidly. This paired with better connectivity revved up the capabilities of the smart building. Now, buildings could integrate more diverse systems and devices. This meant better data collection and remote monitoring.

As time advanced, technological solutions also did. Cloud computing, advanced sensor technologies and more detailed data analytics all combined to add richer levels of intelligence and responsivity.

But now there’s a super-powered technology on the block. It’s fuelling the evolution of the smart building into something that is a lot more adaptive, proactive, energy efficient and ready to provide those all-important personalised occupant experiences that have come to matter so much.

That technology superpower is, of course, artificial intelligence. Combined with machine learning and advanced analytics, it’s starting to make significant waves in the built environment.

AI brings a new level of intelligence and adaptability to smart building systems. It’s making it possible for buildings to learn. To adapt to patterns. To predict maintenance needs, and to optimise energy consumption. And, importantly, it’s redefining the end-user experience, in a head-turning way.

How will AI revolutionise the future of smart buildings?

It’s safe to say smart building technology has done a sterling job to date. Just like 5G upped the ante over 3G by introducing higher data speeds, lower latency and support for a broader range of applications, so artificial intelligence is starting to push smart building tech to the next level.

The traditional smart building relies on rule-based systems, statistical models and reactive automations. But with its machine learning and advanced data analysing capabilities, AI will introduce a multitude of advantages and enhancements, especially in areas such as energy optimisation, predictive maintenance and the personalised experience.

10 examples are:

1. Data-driven decision making

The AI-driven smart building will be able to tap into advanced data analytics to make informed decisions based on both real time and historical data. Thanks to this data-driven approach, decision-making will be based on a higher degree of accuracy. It will also become a lot more adaptive compared to traditional smart tech, which relies on simpler, rule-based systems.

2. Predictive capabilities

Predictive maintenance is an essential component of smart building technology. Enhanced predictive capabilities of AI-driven systems will extend beyond maintenance, into numerous aspects of building management. From resource usage to system performance and occupancy patterns.

3. Customisation to building-specific characteristics

Al-powered systems can be customised to the particular characteristics of a building. AI will quickly learn and share what works, and what doesn’t, in its specific environment.

4. Data merging from multiple sources

Smart buildings generate huge amounts of data from their IoT network of sensors, devices and systems. AI has the ability to seamlessly integrate and analyse data from multiple sources, providing a comprehensive view of the building from a holistic perspective. Its added proficiency in recognising complex patterns through machine learning will allow building managers to clearly see how one or more actions can directly or indirectly affect others.

5. Adaptability and learning

Unlike traditional smart buildings, AI-powered smart buildings will adapt to changing conditions. They will learn from experience, and keep on improving their knowledge. This means the building system will continue optimising its performance, and will respond dynamically to the evolving needs of the building user.

6. Tailoring the user experience

One of the most exciting smart building enhancements coming in on the back of AI has to be the level of personalisation. AI systems can learn individual user preferences for lighting, temperature and other environmental factors, offering a more comfortable and tailor made experience. Whilst traditional smart buildings offer customisation, AI will introduce a much deeper level of granularity and adaptability.

7. Optimising resource usage

AI has the ability to analyse gargantuan datasets in real time. The impact of this ability on resource usage will be significant, extending way beyond utilities and energy efficiency to space, equipment and more. Traditional smart buildings have the power to optimise some building aspects, but AI will shine a light on the bigger picture of building processes, for a more valuable holistic view.

8. Enhancing safety and security

From automated anomaly detection, to facial recognition, behaviour monitoring and predictive analytics, AI has the ability to identify and respond to a host of security threats that traditional building security systems may miss. Tenant and guest will have another layer of security.

9. Integrating with emerging technologies

The artificial intelligence-powered smart building will be better placed to integrate with other new technologies, such as virtual and augmented reality and advanced automation. As a result, buildings will become more technologically advanced and ready to respond to the growing digital-based demands of tomorrow.

10. Ongoing improvement

The fact that AI never stops learning will see AI-driven smart buildings continuously improving over time. As more and more data is collected and analysed, AI-based systems will enhance their performance and efficiency rather than stand still.

So, whilst the smart building has its inherent merits, the adoption of AI will enhance accuracy, efficiency and adaptability, leading to a more intelligent, responsive and user-focused environment.

What important AI trends are set to transform the commercial real estate sector?

Smart building management is one of several emerging AI-driven trends in the commercial real estate sector.

Commercial real estate, buoyed by AI, will undoubtedly experience titanic growth. AI is becoming foundational. A door is opening in commercial real estate, and what lies behind it is not just a pathway towards evolution, but a highway to revolution.

Think about it. You’ve got smart, predictive tech at your fingertips with the power to anticipate market movements, forecast the long term viability of an investment, and proactively see to maintenance issues before they escalate into major problems.

PwC research shows that global GDP could be up to 14% higher in 2030 because of AI. That’s the equivalent of an additional $15.7 trillion, making it the biggest commercial opportunity in today’s fast changing economy.

No doubt, the commercial real estate sector will feel the ripples of these effects.

It’s been refreshing to witness the industry opening up and embracing artificial intelligence-powered technologies. Property management, sustainability, maintenance, operations and decision-making all benefit as a result.

Leading UK investment firm Royal London Asset Management experienced significant improvements in HVAC operations and energy efficiency in an 11,600 square metre commercial office building. By implementing AI-powered technologies, the firm has reached a record ROI of 708% and energy savings of 59%, reducing carbon emissions by up to 500 metric tonnes per year.

(JLL source)

AI, machine learning and sustainable building technologies are anticipated to play a vital role in shaping the future of property investment, management, development and marketing.

Automated valuation models (AVMs), for example, make use of machine learning algorithms to assess property values based on a variety of factors. And there are AI-powered platforms that use match-based algorithms to efficiently connect buyers, sellers, landlords and tenants. These facilitate negotiations and transactions.

But one of AI’s most valuable capabilities has to be the way it can power through vast datasets, analysing them at breakneck speed. AI-derived data insights are endowing property professionals. The ability to make data-driven decisions, providing valuable understanding when it comes to identifying emerging market trends and appraising opportunities.

Digital twins are another emerging trend in the commercial real estate sector. By creating virtual replicas of physical assets, they play a crucial role in enhancing property management and maintenance processes.

These models make use of real time data, simulations and analytics. This AI-driven proptech provides valuable insights, as well as optimising many aspects of property operations, from space utilisation and planning, to predictive maintenance, energy efficiency and risk management.

Digital twins also contribute to enhancing the tenant experience by helping to design personalised and responsive services. They also do a great job of facilitating collaboration between service providers, property management teams and a building’s end users. And that’s something we know, first-hand, can make a huge difference day-to-day.

All these innovations are ripe for adoption in the commercial real estate industry.

Tech Insight: Are AI and machine learning one in the same?

In short, no.

Related as they may be, artificial intelligence and machine learning are definably different aspects of computer science.

AI refers to the creation of intelligent systems with the ability to learn and reason like humans. These systems can undertake tasks such as problem-solving, learning, planning, perception, recognition and language translation.

AI systems are able to adapt to new information and environments, and perform tasks without having to be explicitly programmed to do so in particular contexts.

Machine learning is a subset of artificial intelligence.

Machine learning algorithms learn patterns and relationships from datasets and can improve in performance over time. Once they’ve been trained on an initial dataset, they can make predictions and decisions on new, unseen data. All without further explicit programming.

So, whilst machine learning is a key component of many AI systems, it is not AI itself. AI is the broader concept of creating intelligent machines with near-human characteristics, whilst machine learning is a tool used to achieve AI’s aim of creating intelligent systems.

How will AI be used in the smart buildings of the future?

AI will transform the smart building in so many ways, delivering benefits across the board for building owners, managers, tenants and end users alike.

1.     Improving energy efficiency management

The AI-powered smart building will optimise energy consumption using machine learned automations to adjust heating, lighting and cooling systems based on real time usage and occupancy. It will also react to external factors such as climate and natural light fluctuations.

2.     Boosting the accuracy of predictive maintenance

AI algorithms will predict potential issues with building systems and equipment, extending equipment life and cutting crippling downtime.

Machine learning algorithms will recognise even the most subtle signs of potential failures. A process that might have proved challenging for traditional, rule-based systems to identify.

Even better, as the model receives feedback on its predictions, it will adapt and improve its accuracy over time, leading to progressively dependable maintenance forecasts.

3.     Enhancing the visitor experience

Artificial intelligence will streamline the visitor experience in the future smart building. Guiding visitors through the sign-in process, callers may be greeted by anything from a simple tablet to a robot reception manager.

Visitors will also enjoy wayfinding information delivered direct to their handsets, whilst hosts are automatically notified of their arrival.

4.    Using knowledge as power

One of AI’s most exceptional features, has to be its ability to process and analyse vast swathes of data in real time.

Advanced analytics provide valuable insights into building performance and efficiency. It then scrutinises how resources and spaces are used, as well as highlighting opportunities for improvement and cost savings.

IoT data mining will be used to automate many facilities management tasks, freeing up valuable time to refocus on more meaningful jobs. Things like strategic space planning, costs optimisation and budgeting can be a main focus. They’ll also be able to allocate time to tasks that require a more human feel, such as community engagement, culture and workplace transformation.

How does the future of work look as AI embeds itself into our daily lives?

The integration of AI into our daily lives is transforming the future of work in many ways. From time-saving automation of repetitive tasks, to workplace collaboration and data-driven decision making, AI is becoming embedded into so much of what we do. Soon, it will become invisible. In other words, we’ll all just expect it – and the convenience it brings to our lives – to be there.

And that’s why at Smart Spaces® we believe that integrating artificial intelligence into the smart building of the future is so important.

The AI-powered smart building will directly benefit its tenants. It’s also set to make buildings more appealing and easier to manage, translating as added value for landlords and property managers.

We must never forget that at the heart of it all, we have the end user. Those who use the building day in, day out. Often spending as much time in it as they do in their homes.

The end user experience is a vital consideration at all levels. From the occupants and visitors themselves, to their employers and hosts, and the landlords who have no choice but to factor it in. That’s if they’re going to compete within today’s competitive commercial real estate landscape.

And this is what we see as the most exciting part of the evolution of the smart building. Quite possibly the greatest value AI can bring to smart technology has to be what it can do for the tenant experience.

We already know that AI will make it possible to personalise the working environment based on individual preferences, like boosting well-being and comfort.

But AI will also bring with it the digital concierge, set to be a welcome feature as workplaces start to incorporate more ‘lifestyle experiences’ in an effort to create that home-from-home feel at work.

Arranging break time or after work activities becomes a breeze. The concierge app uses machine learning to suggest sessions, classes and events based on past bookings.

The AI-powered concierge can also handle desk and meeting room bookings with ease, incorporating machine-learnt personal preferences, such as quiet areas, natural light or being seated close to colleagues.

Employee chatbots are another feature set to become embedded into the workplace of the future. Designed to simulate conversations with employees, the chatbots use natural language processing (NLP) and AI to understand and respond to user queries and requests in human-like fashion.
These bots will be able to:

  • provide quick access to company-based information
  • support training and development initiatives
  • connect users to intranets and staff portals
  • act as a technical support desk
  • assist with HR-related queries
  • organise transport

There will be almost endless scope for this AI-powered feature. That’s the benefit of machine learning.

The future of commercial real estate is not just smart – it’s ‘AI smart’

The future of the smart building, and of commercial real estate in general, is unquestionably interlinked with artificial intelligence.

The sector is a highly competitive arena, with no leeway for missed opportunities. The tenant and end user experience have never mattered more. And, in our opinion, AI is the technology with the power to deliver a matchless edge.

Those who explore its potential and go on to embed it into their everyday operations and allow it to drive their planning will be the ones who come out on top as industry successes.

Smart Spaces is a fully customisable Internet of Things (IoT) and artificial intelligence powered platform.

We transform a traditional building management system into a smart building management system.

To learn more about how our tailored technology could help transform the end user experience within your building, please get in touch.

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