Digital twins, which are real-time virtual replicas of physical systems, have gained significant traction over the past decade. These digital counterparts allow for enhanced data monitoring, simulations, predictive analytics, and collaborative efforts. Despite their potential, high costs, scalability, and complexity have hindered widespread adoption. Startups are now tackling these challenges and opening new avenues in fields such as climate risk forecasting, factory floor planning, predictive precision medicine, and business process simulation.
Ten years ago, the concept of digital twins was mostly theoretical, with limited practical applications. Initial attempts faced hurdles due to the high costs associated with creating and maintaining these virtual models. Moreover, the technology was often seen as complex and difficult to integrate into existing systems. However, advancements in AI, IoT, and data analytics have gradually addressed these issues, making digital twins more accessible and practical. The latest trends show startups taking an agile approach to exploit new commercial opportunities, thereby overcoming earlier limitations.
In particular, companies like Twinsity and Slingshot Simulations are leading the charge. Twinsity, based in Germany, provides a platform called TWINSPECT for creating photorealistic 3D models and conducting AI-assisted damage analysis through drone inspection data. This tool improves communication and decision-making by offering detailed inspection data accessible from anywhere. The company has secured €2.8 million in funding to support its initiatives.
Innovative Approaches and Funding
Slingshot Simulations from the UK offers a cost-effective solution known as Compass: Engine, which builds simulations of real-world objects and systems. This technology enables rapid visualization and analysis of vast datasets, helping users gain insights much faster. Slingshot Simulations has collaborated with the Department for Transport on a city-scale project to assess the impacts of low emission zones. They have raised £5.3 million to further develop their technology.
Open Space, another UK-based firm, has developed a people-centric digital twin platform. It uses computer vision, AI, IoT, and gaming technology to offer data-driven insights into people flow challenges for cities, transport providers, and retailers. The platform enhances safety and customer experience through real-time pedestrian simulation and predictive analytics. Open Space’s technology is operational at the St Pancras mobility hub.
Expanding Use Cases Beyond Industry Norms
Bulgaria’s MYX focuses on creating digital twins for the telecommunications sector, particularly aiding the 5G rollout. Their software uses data from drones and imaging technologies to provide detailed insights into assets like telecom towers and cities. This helps companies make informed decisions regarding their infrastructure.
Praedico from the Netherlands specializes in rail systems, creating digital twins to centralize and structure data. This platform offers a unified source of truth for smart asset management, reducing maintenance costs and improving track availability. Tomorrow Things in Germany offers an intelligent automation platform to create digital twins of technical assets, optimizing production lines and predicting potential issues. Their unique blueprint technology facilitates seamless integration of digitalized assets, enhancing interoperability within the ecosystem.
The growing adoption of digital twins across various industries highlights the technology’s transformative potential. Startups are instrumental in overcoming challenges related to cost, scalability, and complexity, making these virtual models more accessible. As technology continues to evolve, digital twins will likely play an even more significant role in enhancing operational efficiencies and decision-making processes across different sectors. Readers interested in the latest technological advancements should keep an eye on these emerging trends and companies.