Overcoming Building Sector Emissions With AI-Powered Solutions

The building sector plays a significant role in climate change, contributing up to 37 percent of energy-related CO2 emissions. As half of today's buildings are projected to remain in use until 2050, there is an urgent need to upgrade these structures to achieve the 2030 decarbonisation targets. While this challenge is significant, net-zero energy buildings (NZEBs) offer a clear and effective solution. 

NZEBs, also known as zero-energy buildings, are structures that produce as much energy as they consume, resulting in a net-zero carbon footprint. These buildings utilise cutting-edge technologies to minimise their energy demand while maximising energy generation from sustainable sources such as solar, wind, and geothermal power. 

Although existing technologies are advancing, there remains a crucial need to shift from manual methods to smart, automated solutions. Technologies such as artificial intelligence (AI), the Internet of Things (IoT), blockchain, Building Information Modeling (BIM), and advanced analytics—including cloud and edge computing—have the potential to revolutionise energy monitoring in buildings. Adopting these innovations will drive improvements in energy efficiency and significantly impact climate change mitigation. 

Research indicates that many patented innovations address significant challenges such as inefficient energy use, lack of real-time monitoring, and high operational costs by developing advanced solutions that integrate sophisticated analytical models. 

Recent patents showcase key advancements in AI-based NZEB solutions. For instance, South Korea’s KT Corp has developed an AI-driven energy control method using machine learning and virtual models to optimise energy use. This method collects and processes real building data, corrects parameters with a virtual mini-clone model, and trains using both real and virtual data, enabling real-time control applicable to any building type. Similarly, European NEC Labs has introduced a method for improving machine learning models through knowledge infusion, enhancing their performance and versatility. China-based Wuhan University has developed an energy-saving building control method based on real-time requirements, optimising energy use across buildings through a control module, achieving low-carbon, energy-efficient operation and maintenance for entire building groups. 

Advancements in BIM are reflected in China’s Guangdong Guanxiong Construction Group’s development of a BIM-based holographic system that creates 3D building models for visual monitoring and fault detection, thus improving NZEB energy efficiency. 

Moreover, South Korean Nextcore Technology has created an IoT-based data integration system that analyses and filters diverse data types from various sources, converting them into actionable insights through a unified terminal. This system can automatically interface and monitor data patterns via wired and wireless communication, enhancing real-time management and efficiency for NZEBs. 

Additionally, the Korea Institute of Energy Research has introduced a blockchain-based system to improve energy efficiency by forecasting energy needs and managing heat storage, with data sent to a power grid server for demand response and blockchain-recorded contracts, enhancing overall energy management and coordination. 

For NZEBs, integrating AI and data analytics is critical. It is not just about having the latest patents or technologies; the digital maturity of these solutions is equally important. Technologies must be validated and proven through lab-scale and industrial applications to ensure their effectiveness and scalability. While digital maturity remains a concern for patents and research-based models, both established companies and startups are actively exploring AI and digital solutions for NZEBs, showcasing their practical applications and effectiveness in real-world scenarios. For instance:

Siemens' Building X Energy Manager integrates building data into a unified AI-powered platform to streamline operations and optimise energy use, supporting NZEB goals. 

Kiona's Edge AI Solution is a cloud-based platform that improves the heating efficiency of buildings by analysing real-time data on temperature, humidity, and weather conditions, enabling more precise and effective energy management for NZEBs. 

vadiMAP provides an energy management platform that uses an online questionnaire and photos to analyse data and recommend solutions, helping users optimise energy use, manage costs, and support NZEB goals.

Community Energy Labs (CEL) offers a virtual engineer through their IoT and SaaS platforms to continuously monitor and adjust energy use, supporting NZEB efficiency and decarbonisation efforts. 

BrainBox AI's ARIA provides predictive insights and real-time data integration, aiming to reduce HVAC energy costs and greenhouse gas emissions in NZEBs.

In addition to these innovations, government-funded projects are also playing a crucial role. They emphasise the urgent need for research and development in advancing NZEBs and addressing climate change through effective sustainability solutions. For example, the ZEBAI project, supported by €3.8 million from the European Commission, aims to transform zero-emission building design by testing new methods across Europe. Similarly, UWE Bristol, with £800,000 from Innovate UK, is developing AI software to quickly identify low-carbon materials, integrating with building design systems to enhance efficiency and meet net-zero carbon targets. 

(Darshana Naranje, Senior Analyst, Technology Research & Advisory, Aranca.)