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Improving Sustainability in the Built Environment through AI

29 Jan 2024

The built environment is a leading contributor to emissions. Sustainable buildings are necessary.

Without improving sustainability in the built environment, ESG initiatives will struggle to meet set targets. As with many sectors, the growth of AI is leading hopes for driving a lot of these, much needed, energy optimisations.

But what exactly does AI bring to the process of preventing the depletion of natural or physical resources so that future generations can continue to benefit from them? In other words, how can artificial intelligence be used to create tangible sustainability solutions?


AI and sustainability: what we know

We know that sustainability fuses environmental, social and economic aspects. That it’s an important process that seeks to address the environmental challenges the planet is facing, as well as promoting social equality and securing economic buoyancy. We also know that the aim of sustainability is to secure a safer, healthier and more fulfilling future for all, both in the short term, and for generations to come.

In terms of artificial intelligence, we’re aware that it’s a sophisticated technology that can mimic aspects of human intelligence, and help make informed decisions.

AI encompasses machine learning, a process that enables systems to learn from experiences and data, improving and adapting over time without programming. It can also process enormous swathes of information, identifying patterns and anomalies and triggering automated actions.

Something else we know is that the phrase ‘AI and sustainability’ is becoming increasingly common. It reflects the burgeoning interest in the use of artificial intelligence to support sustainable strategies and development. Making use of AI to address environmental and social challenges is a trend that’s evident across media coverage, academic literature and industry discussions.

We also know that buildings are responsible for 36% of global final energy use, as well as 39% of energy and process-related carbon dioxide emissions (International Energy Agency).

Armed with all this knowledge, let’s explore how AI can be used to make genuine changes to a building’s sustainability efforts and net zero ambitions?


How can AI support sustainability in the built environment?

Energy consumption management.

Workplace comfort monitoring.

Renewable energy integration.

Resource management.

Waste reduction.

These are just some of the tangible ways in which AI can support sustainability in the built environment. But how exactly does the built environment draw on these capabilities?

In short, it’s all about integrating AI into smart building technology. In doing so, we create a super power. A highly sophisticated system with the ability to draw on advanced data analytics to process and interpret vast amounts of information from connected devices and sensors, and to make use of machine-learnt processes, reactions and automations.

All of this allows for real time optimisation of a variety of building functions, cultivating efficiency, cost savings, energy usage optimisation and enhanced user experiences within the built environment, and contributing to sustainability efforts. Let’s drill that down a bit further.


Here are 9 ways AI can optimise the built environment:

1. Energy consumption management

AI uses advanced algorithms and data analytics to boost the efficiency of a building’s energy-related processes and systems.


2. Predictive analytics

Predictive analytics are used to forecast and analyse energy use patterns based on historical data, climatic conditions and other related factors.

By gaining a good understanding of how energy is consumed and when, AI-based systems are able to anticipate peak demand times, and suitably optimise building operation systems.


3. Occupancy sensors

AI works alongside occupancy sensors to respond dynamically to changing numbers within the various zones of a building.

Empty or low-occupancy areas will automatically cut energy consumption, for example by adjusting lighting levels or reducing HVAC settings so that energy is saved, without any compromise on occupant comfort or building safety.


4. Equipment operation

When it comes to choosing and operating equipment, AI can help by analysing performance data against specific needs, and recommending choices and improvements.

By way of an example, AI has the ability to automatically optimise HVAC system performance by making adjustments to temperature and airflow, based on real time occupancy and environmental conditions. It can also automatically reduce interior lighting when outdoor natural light increases, and vice versa.


5. Fault detection and maintenance

By constantly monitoring performance and relaying anomalies picked up by sound and vibration sensors, AI systems can efficiently and quickly identify developing faults or inefficiencies in building systems, machinery or plant.

Early detection of potential problems means proactive maintenance replaces reactive maintenance, preventing energy waste, ensuring optimal machinery operation, and prolonging equipment life.

6. Integrating renewable energy sources

Artificial intelligence has the ability to support the integration of renewable energy sources into a building. By optimising usage based on energy demand and climatic conditions, AI can help get the most out of the power generated by these eco-friendly sources.

One of the most powerful aspects of AI is that it can be trained on specifics, and will continue to learn over time. So for example, it can learn the energy consumption patterns of a building at different times of the day or during different seasons, and set precedents for energy usage optimisation that align with those.


7. Energy usage monitoring

AI generates detailed insights into energy usage patterns. Building and facilities managers can tap into this information to identify areas ripe for improvement. This will support them in creating targeted strategies to further enhance the way energy is used throughout the building, reducing carbon footprint and assisting in the move towards net zero.


8. Waste reduction

AI algorithms connect with smart monitoring systems to track the use of resources, delivering insights into usage patterns that can be used to inform improvement strategies.

AI-driven smart inventory systems help to efficiently manage supplies. They have the ability to predict demand for resources, ensuring excess inventory is avoided and cutting the likelihood for waste as a result of unused or expired items.

AI can also be used to track the use of utilities. Machine learning will identify irregularities, such as unusually high water consumption, prompting checks to be made for leaks or other problems.

Artificial intelligence also makes it possible to continuously monitor waste generation and management processes within a building. The detailed data and reports produced empower building managers to implement tailored waste reduction and recycling strategies.


9. Workplace well-being

Sustainability isn’t just about the environmental aspects, important as they are. It’s also about supporting the health and well-being of the occupants of a building.

Artificial intelligence makes it possible to transfer control of the likes of lighting, heating and cooling directly into the hands of the end user, allowing them to set their own preferences for their immediate working environment.

AI will also monitor indoor air quality and, through machine learning, detect anomalies that could jeopardise occupant health. It will also prompt changes to outdoor air flow rates in line with changes in occupancy or outdoor pollution levels.


What next for AI and sustainability?

Research by PwC UK, commissioned by Microsoft, estimates that using AI for environmental applications could contribute up to $5.2 trillion USD to the global economy in 2030, a 4.4% increase relative to business as usual.

What’s more, the research reveals that the application of AI could reduce worldwide greenhouse gas (GHG) emissions by 4% in 2030, an amount equivalent to 2.4 Gt CO2e – the same as the 2030 annual emissions of Australia, Canada and Japan combined.

Artificial intelligence is already playing a crucial role in supporting sustainability. In the built environment specifically, by providing rich, data driven insights, and through predictive analytics and real time monitoring, AI makes it possible for buildings to operate in a more streamlined fashion, optimising energy consumption and enhancing workplace well-being, as well as identifying opportunities for the improvement of overall environmental impact.

The beauty of artificial intelligence in the context of sustainability lies in the way it transforms data into actionable strategies, supporting building owners in making informed decisions that result in long term sustainability.

We see the role of AI in sustainability epitomised by its ability to significantly transform traditional approaches to building management into something considerably more sophisticated, supporting a future that’s greener, healthier, more stable and a great deal more resilient.

AI-powered smart building retrofitting can play a pivotal role in reducing the energy consumption of the UK’s existing building stock, which is where we know the primary focus needs to lie if net zero targets are to be met.

Smart Spaces is an Internet of Things (IoT) and artificial intelligence powered platform that transforms a traditional building management system into a sophisticated smart building management system. To learn more about how our fully customisable technology could help drive sustainability within your building, please get in touch.

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