How AI helps slash CO2 emissions and energy use in buildings

Combining AI with IoT solutions allows building owners and managers to sharpen building performance. Here’s why.
San Fransisco skyline at night

Smart buildings employing interconnected digital and automation technologies to optimise performance are widely recognised as being the key to decarbonising our built environment and reducing the impact of climate change.  

The scale of the problem

The International Energy Agency 2020 Global Status report suggests that building construction and operations are responsible for 38% of global energy-related CO2 emissions and a - record-high - 28% of energy-related CO2 emissions.

The need to decarbonise our built environment - utilising AI and IoT - was put into the spotlight at the COP27 climate conference in 2022. More than 140 of the events focused attention on the impact and future of real estate and construction.  

Intelligent technology plays a significant role in ensuring the long-term viability and sustainability of our built environment which needs to achieve Net Zero emissions by 2050.  

Incorporating smart approaches in our built environment enables managers to monitor and leverage every aspect of their facility’s management: from HVACR (heating, ventilation, air conditioning and refrigeration) and energy use and allocation to indoor air quality (IAQ) and comfort levels.  

AI allows operators to take these capabilities to the next level - for even greater optimisation and decarbonisation.  

How does AI enable smart capabilities?

AI is already embedded in many aspects of our lives: from the way we enjoy social media and entertainment streaming to how we shop for products and services.  

Within the built environment, AI has the potential to fast-track our collective journey to carbon neutrality. The Capgemini Research Institute suggests AI is likely to reduce total GHG (greenhouse gas) emissions by 16% by 2030 and is expected to enable organisations to fulfill up to 45% of targets set out by the Paris Agreement.

Take HVAC systems, for example.  Since HVAC and lighting typically account for around half of energy use in commercial properties, centralising and automating controls significantly reduces energy waste.  

When structures rely on a basic thermostat (no AI or programmability), a temperature is set and when the temperature deviates from this the system automatically triggers heating or cooling via an electrical connection.

Leveraging AI enables existing HVAC equipment to analyse billions of data points -allowing it to learn, reason and solve issues. Say you have an office lobby with revolving doors. Standard HVAC systems would waste energy struggling to manage the fluctuating temperatures in this area. Incorporating AI allows the system to learn, adapt and react to this ever-changing area for cost-efficient HVAC management.  

Machine learning means AI can not only identify that an office’s common spaces grow warmer at break times as workers gather: it also proactively adapts and adjusts to this ahead of break times for maximum comfort levels.  

Teaching old buildings new tricks

Smart capabilities are often featured in our newest structures. But what about our existing structures?

Experts suggest that around 80% of the buildings around us will still be in use in 2050 and many - >80% - are not suitable for the controls offered by Building Management Systems (BMS).

That’s why Novacene developed its innovative and affordable approach to measuring, managing and controlling building performance in our existing built environment.

Put to the test in buildings around the world, Novacene has enabled operators to benefit from smart capabilities - whether their building is brand-new or hundreds of years old.

Facilities include:




Heritage sites

Social housing

Combatting climate change

Seamlessly integrating a building’s facility systems (eg HVAC, lighting) with a smart, autonomous, AI-enabled solution like Novacene’s gives organisations and their managers a clear overview of their infrastructure’s efficiency and effectiveness.  

Armed with data - in context - allows managers to take the actions needed to reduce energy use, cut emissions and costs, and shrink their carbon footprint.

Increasingly, AI is taking decision-making out of the hands of workers. Saving time and resources in this way allows efficiency and climate-driven organisations to focus on more important work activities.

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