Digital Twins for Sustainability

Detailed overview of innovation with sample startups and prominent university research

What it is

Digital twins for sustainability are virtual representations of physical assets, systems, or processes that incorporate environmental and sustainability data. These digital twins go beyond traditional models by including information on energy consumption, emissions, resource usage, and other sustainability metrics. This allows organizations to monitor, analyze, and optimize their operations for improved environmental performance.

Impact on climate action

Digital Twins for Sustainability under Digital for Decarbonization revolutionize climate action by providing virtual replicas of physical assets and processes. By enabling real-time monitoring, optimization, and predictive analytics, these innovations enhance resource efficiency, reduce emissions, and accelerate the transition to a sustainable, low-carbon economy.


  • Digital Twin Technology: Digital twins are created using 3D modeling, simulation software, and data from various sources, such as sensors, IoT devices, and enterprise systems.
  • Sustainability Data Integration: Environmental and sustainability data, such as energy consumption, emissions, and resource usage, are integrated into the digital twin model.
  • Life Cycle Assessment (LCA): LCA tools can be used to assess the environmental impacts of a product or process throughout its lifecycle, and this data can be incorporated into the digital twin.
  • AI and Machine Learning: AI and ML algorithms can be used to analyze sustainability data, identify patterns and trends, and recommend optimization strategies.
  • Visualization and Reporting: Data visualization tools are used to present sustainability data and insights in a clear and understandable way, enabling stakeholders to make informed decisions.

TRL : 5-7

Prominent Innovation themes

  • Sustainability-Focused Digital Twin Platforms: Startups and software companies are developing digital twin platforms specifically designed for sustainability applications, integrating environmental data and providing tools for sustainability analysis and optimization.
  • AI-Powered Sustainability Analytics: AI and machine learning are being used to analyze sustainability data and provide insights into emission reduction opportunities, resource efficiency improvements, and other sustainability metrics.
  • Integration with Building Management Systems (BMS) and Industrial Control Systems (ICS): Digital twins are being integrated with BMS and ICS to provide a more holistic view of building and industrial operations and enable real-time optimization for sustainability.
  • Circular Economy Applications: Digital twins can be used to model and optimize circular economy strategies, such as closed-loop manufacturing and industrial symbiosis.

Other Innovation Subthemes

  • Digital Twin Platforms for Green Buildings
  • Integration of Digital Twins with Building Management Systems
  • Circular Economy Modeling with Digital Twins
  • Digital Twins for Sustainable Urban Development
  • Predictive Maintenance for Renewable Energy Infrastructure
  • Sustainability Optimization in Industrial Processes
  • Real-time Energy Efficiency Monitoring with Digital Twins
  • Environmental Impact Assessment via Digital Twin Technology
  • Smart Cities Planning and Optimization Tools
  • Resource Efficiency Improvement Strategies with Digital Twins
  • Energy Consumption Reduction Techniques with Digital Twins
  • Waste Reduction and Recycling Optimization with Digital Twins
  • Climate Change Mitigation Strategies with Digital Twin Technology
  • Sustainable Agriculture Management through Digital Twins
  • Water Conservation and Management Solutions
  • Green Transportation Infrastructure Planning with Digital Twins

Sample Global Startups and Companies

  1. ThoughtWire:
    • Technology Enhancement: ThoughtWire offers a digital twin platform focused on creating smart and sustainable built environments. Their platform integrates real-time data from various sources, including IoT sensors, building management systems, and energy monitoring devices, to create a virtual representation of buildings and urban spaces. This digital twin enables predictive analytics, scenario modeling, and optimization of sustainability strategies.
    • Uniqueness of the Startup: ThoughtWire stands out for its focus on creating intelligent and connected environments that prioritize sustainability, occupant well-being, and operational efficiency. Their digital twin platform provides actionable insights and recommendations for optimizing energy usage, reducing carbon footprint, and enhancing overall sustainability performance.
    • End-User Segments Addressing: ThoughtWire serves real estate developers, building owners, facility managers, and smart city initiatives seeking to enhance sustainability and resilience in the built environment. Their digital twin solutions are deployed in commercial buildings, healthcare facilities, educational campuses, and urban infrastructure projects worldwide.
  2. Cityzenith:
    • Technology Enhancement: Cityzenith offers a 5D Smart City digital twin platform that integrates data from multiple sources to create a comprehensive and interactive model of urban environments. Their platform enables urban planners, city officials, and stakeholders to visualize, analyze, and optimize sustainability initiatives such as energy efficiency, renewable energy integration, and carbon emissions reduction.
    • Uniqueness of the Startup: Cityzenith stands out for its focus on creating digital twins specifically tailored for smart and sustainable cities. Their platform provides a user-friendly interface and advanced analytics capabilities, empowering cities to make data-driven decisions and achieve their sustainability goals effectively.
    • End-User Segments Addressing: Cityzenith serves municipal governments, urban planners, architects, developers, and infrastructure investors involved in smart city projects. Their digital twin solutions support sustainability initiatives across various sectors, including transportation, energy, water, waste management, and urban development.
  3. Akselos:
    • Technology Enhancement: Akselos specializes in predictive digital twins for critical infrastructure assets such as offshore platforms, wind turbines, and bridges. Their platform utilizes physics-based modeling, advanced analytics, and machine learning algorithms to create highly accurate digital twins that predict asset performance, identify potential risks, and optimize maintenance strategies.
    • Uniqueness of the Startup: Akselos stands out for its expertise in creating high-fidelity digital twins that can simulate complex physical behaviors and environmental conditions. Their platform enables asset owners and operators to improve sustainability by maximizing asset lifespan, reducing downtime, and minimizing environmental impact through optimized operations and maintenance.
    • End-User Segments Addressing: Akselos serves asset-intensive industries such as energy, utilities, and infrastructure, where sustainability and reliability are paramount. Their digital twin solutions are deployed by asset owners, operators, and engineering firms seeking to enhance asset performance, safety, and resilience while minimizing environmental footprint and total cost of ownership.

Sample Research At Top-Tier Universities

  1. Massachusetts Institute of Technology (MIT):
    • Research Focus: MIT is at the forefront of research on Digital Twins for Sustainability, focusing on developing advanced modeling and simulation platforms to create virtual replicas of physical assets, systems, and environments for optimizing resource efficiency, reducing emissions, and enhancing sustainability.
    • Uniqueness: Their research involves integrating real-time sensor data, IoT technologies, and predictive analytics algorithms to continuously monitor and analyze the performance, condition, and environmental impact of buildings, infrastructure, and industrial processes. They also develop decision support systems and scenario planning tools to identify opportunities for energy savings, emissions reductions, and operational improvements.
    • End-use Applications: The outcomes of their work find applications in urban planning, smart buildings, and industrial automation. By leveraging Digital Twins for Sustainability, MIT’s research supports data-driven decision-making, infrastructure resilience, and carbon footprint reduction, contributing to the transition to a low-carbon and sustainable society.
  2. Stanford University:
    • Research Focus: Stanford University conducts pioneering research on Digital Twins for Sustainability, leveraging its expertise in computer science, data analytics, and environmental engineering to develop innovative approaches for modeling, monitoring, and optimizing complex systems for sustainability outcomes.
    • Uniqueness: Their research encompasses the development of scalable, interoperable, and user-friendly digital twin platforms that enable stakeholders to visualize, analyze, and collaborate on sustainability initiatives across diverse domains, including energy, water, transportation, and agriculture. They also explore the integration of AI, machine learning, and blockchain technologies to enhance the accuracy, reliability, and security of digital twin applications.
    • End-use Applications: The outcomes of their work have applications in smart cities, renewable energy integration, and natural resource management. By harnessing Digital Twins for Sustainability, Stanford’s research empowers decision-makers to assess the environmental impact of policies, investments, and interventions, facilitating the transition to a more sustainable and resilient future.
  3. National University of Singapore (NUS):
    • Research Focus: NUS is engaged in innovative research on Digital Twins for Sustainability, leveraging its expertise in urban planning, environmental science, and information technology to develop holistic solutions for enhancing resource efficiency and environmental resilience.
    • Uniqueness: Their research involves developing digital twin models of cities, buildings, and ecosystems to simulate and optimize energy consumption, water usage, waste generation, and greenhouse gas emissions. They also explore participatory modeling approaches and citizen engagement strategies to promote sustainability awareness, behavior change, and community resilience.
    • End-use Applications: The outcomes of their work find applications in sustainable urban development, climate adaptation, and disaster risk management. By deploying Digital Twins for Sustainability, NUS’s research supports evidence-based decision-making, stakeholder collaboration, and policy innovation, driving progress towards a more sustainable and livable environment.

commercial_img Commercial Implementation

Digital twins for sustainability are being implemented by companies and organizations across various industries, including manufacturing, construction, and energy. For example, Siemens is using digital twins to optimize the energy efficiency of its buildings, while Schneider Electric is using digital twins to improve the sustainability of its supply chain.