Embrace the Future Mastering Digital Twins for success
Conversations around topical research papers in computer engineering brought to you by @CodeandCircuits
Digital twins are virtual representations of physical objects, processes, or systems that enable real-time monitoring, simulation, and optimization. They integrate sensor data, simulation models, and analytics to mirror the behavior of their physical counterparts, allowing for predictive maintenance, scenario testing, and data-driven decision-making.
Further Reading:
Boyes, H., & Watson, T. (2022). Digital twins: An analysis framework and open issues. Computers in Industry, 143, 103763.
Sharma, A., Kosasih, E., Zhang, J., Brintrup, A., & Calinescu, A. (2022). Digital twins: State of the art theory and practice, challenges, and open research questions. Journal of Industrial Information Integration, 30, 100383.
Juarez, M. G., Botti, V. J., & Giret, A. S. (2021). Digital twins: Review and challenges. Journal of Computing and Information Science in Engineering, 21(3), 030802.
Mihai, S., Yaqoob, M., Hung, D. V., Davis, W., Towakel, P., Raza, M., ... & Nguyen, H. X. (2022). Digital twins: A survey on enabling technologies, challenges, trends and future prospects. IEEE Communications Surveys & Tutorials, 24(4), 2255-2291.
Channel relevance:
Digital twins are highly relevant to computer engineering as they enable the simulation, testing, and optimization of complex systems, products, and processes, allowing engineers to validate designs, predict performance, and drive continuous improvements before physical implementation.