Summary of Digital Twin in Industries: a Comprehensive Survey, by Md Bokhtiar Al Zami et al.
Digital Twin in Industries: A Comprehensive Survey
by Md Bokhtiar Al Zami, Shaba Shaon, Vu Khanh Quy, Dinh C. Nguyen
First submitted to arxiv on: 29 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a comprehensive survey on Digital Twin (DT) technology and its applications across various industrial sectors. DT seamlessly integrates real-world systems with their virtual counterparts, bridging the physical and digital realms. The authors investigate and analyze the capabilities of DT in industries such as manufacturing, healthcare, transportation, energy, agriculture, space, oil and gas, as well as robotics. Key enabling technologies for DT include data sharing, data offloading, integrated sensing and communication, content caching, resource allocation, wireless networking, and metaverse. The paper also delves into real-time data communications between physical and virtual platforms to enable industrial DT networking. Furthermore, the authors extensively explore and analyze major privacy and security issues in DT-based industries. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research paper explores Digital Twin (DT) technology, which connects the physical world with its digital twin. Imagine having a perfect replica of your factory or hospital that you can control and improve remotely. This technology is transforming many industries like manufacturing, healthcare, transportation, energy, agriculture, space, oil and gas, and robotics. The authors look at how DT is used in these industries to improve efficiency, productivity, and decision-making. They also discuss the challenges of keeping this technology secure and private. |
