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Combining the Power of Digital Twins and AI for a Sustainable Future

Originally published by EE|Times Asia

Emerging technologies such as digital twins and artificial intelligence (AI) have the potential to accelerate sustainability for organizations making it a top priority. Unfortunately, they often need to catch up in several areas, including achieving net-zero emissions goals.   

For example, one-third of Europe’s leading companies have pledged to reach net-zero emissions by 2050, according to Accenture. Yet the firm also found that only 9% of companies are currently on track to achieve this objective.

However, by using emerging technologies such as digital twins and AI, organizations can reach net zero and address other sustainability efforts more quickly. These technologies provide companies with valuable insights into their operations that can support sustainability improvements and help them meet their climate goals. For instance, digital twins can test various scenarios and help companies determine the best strategies for reducing energy consumption and emissions.

Technological innovations accelerate digital twin adoption

Digital twin technology has already been deployed in various ways. For instance, by helping healthcare researchers create highly accurate models of the heart, lungs, or other organs to improve clinical diagnoses, education, and training. The energy industry also offers numerous use cases for digital twins, including building digital models to guide oil drilling efforts in real time.

With recent technology advances in simulation and modeling capabilities, increased deployment of IoT sensors, and more widely available computing infrastructure, companies can expand their reliance on digital twins. When an organization augments digital twins with AI, it can realize further uses, such as running simulations to investigate “what-if” scenarios to gain a richer understanding of cause and effect.

There are many possibilities on how these technologies can enhance operations, including their capacity to advance a greener world. Below are a few use cases demonstrating how digital twins and AI facilitate sustainability improvements across industries.

Intelligent industry

It is projected that by 2025 89% of all IoT platforms will include digital twins, altering how industrial and manufacturing operations work because of the detailed insights they will have to enhance sustainability efforts. 

Here are some examples: 

  • Exploring ways to decrease energy consumption through a better understanding of where energy loss is happening
  • Using predictive analytics to decide how to reduce emissions by making adjustments
  • Carrying out risk assessments to detect operational weaknesses that might cause accidents that have an environmental impact

GE Digital is one example of how an organization can apply digital twins and AI to improve sustainability. Using  Autonomous Tuning Software, the company develops a digital twin of its gas turbines to find optimum flame temperature and fuel splits. The software can detect environmental and physical degradation changes in real time, enabling automatic adjustments to ensure that the gas turbines operate efficiently at low emissions and acoustic levels. As a result, power generation plants have reduced carbon monoxide by 14% and nitrous oxide emissions by 10% – 14%.

Intelligent municipalities

Another area poised to transform is city planning, management, and optimization utilizing the combined power of digital twins and AI. These intelligent cities offer several benefits, such as tackling food insecurity, increasing mobility, and helping root out criminal activity.  
With digital twins and AI, city governments can realize, quantify, and predict the effect of their decisions on the environment and test likely scenarios to determine the most environmentally advantageous situation.

For instance, Transport for London (TfL) uses digital twins to gather data on noise, heat, and carbon emissions throughout London's Tube network. Before deploying the technology, TfL staff could only inspect assets when the Underground was closed between 1 am-5 am. With the real-time network access afforded by the digital twin, they can now assess locations throughout operating hours and see data previously undetected by the human eye, such as faults, heat, and noise hotspots. Officials believe the project will be a crucial component of Mayor Sadiq Khan’s goal of a zero-carbon rail system by 2030.

As carbon neutrality becomes a priority for cities across the globe, expect the usage of digital twins and AI to increase.

Intelligent buildings

Just as digital twins and AI can help city sustainability efforts, they are also increasingly being utilized to create intelligent buildings. The technologies ensure sustainability is a priority from the outset, enabling construction managers and other stakeholders to emulate and evaluate a building’s anticipated carbon footprint during the design phase.

When designing The Hickman in London, developers took this approach which is the world’s first building to receive a SmartScore Platinum rating for intelligent buildings. During construction, the digital twin was connected with the facility’s management system through various sensors, providing an integrated view of data such as energy consumption, occupancy, temperature, light levels, and air quality. This empowered the developers to optimize energy performance and reduce carbon emissions and positioned the framework for future sustainability enhancements, as these can be simulated first via The Hickman digital model.

Regulatory pressure to design greener buildings continues to grow in the construction industry, and more developers will likely follow The Hickman path and consider sustainability concerns before building.

Becoming a more sustainable industry and, ultimately, the world has been a tenuous goal for the last several years. But with recent AI innovations and increased adoption of digital twins, this vision is ready to become a reality. Now is the time for companies to exploit the combined power of these technologies to gain insights at every stage of operations to support a more sustainable, less carbon-intensive economy at a micro-level — and a greener planet.