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Synergistic Digital Twins / IoT Systems

Published: November 2025

Digital twins are virtual representations of physical objects or systems that, in combination with IoT technologies, enable precise monitoring, analysis, and optimization in real time. The synergistic implementation of digital twins and IoT systems enables more effective management of various complexities. It improves real-time monitoring and predictive maintenance, optimizes resource utilization, and supports data-driven decision-making in real time. This integration also promotes scalability and flexibility, enhances security and risk management, and facilitates efficient data integration and analysis.

Guiding questions

  • How can Digital Twins and IoT technologies be effectively integrated into existing infrastructures and processes?
  • What role do AI and machine learning play in the further development of Digital Twins?
  • How can interoperability between different Digital Twin systems and IoT platforms be improved?
  • What ethical considerations must be taken into account when implementing Digital Twins in sensitive areas such as healthcare?
  • How can SMEs benefit from Digital Twin technologies without having to make excessive investments?

Challenges

Challenges lie in overcoming isolated data silos, scalability to large and complex systems, and protection against cyberattacks, especially when integrating IoT and Digital Twins. The development of uniform standards is essential to implement Digital Twins across industries. Additionally, protecting sensitive data, for example in smart homes or healthcare, requires special attention. Despite these hurdles, this technology offers companies the opportunity to better understand, control, and optimize complex systems, leading to greater efficiency, cost savings, and innovation.

Concrete examples

  • Inspection of infrastructures
  • Optimization of building performance in facility management
  • Manufacturing in smart factories
  • Energy systems and smart homes

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Reference

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Reference

Michel Reichardt

Michel Reichardt Project Manager Strategic Foresight

Christoph Grollman

Christoph Grollman Project Manager Strategic Foresight

Dr. Sophia Gänßle

Dr. Sophia Gänßle Project Manager Data Science Strategic Foresight

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