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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | UNDERSTANDING THE APPLICATION OF DIGITAL TWIN TECHNOLOGY IN DIFFERENT FIELDS |
| Authors Name: | Divya P , PravithaC P |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_181502
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| Published Paper Id: | IJNRD2205124 |
| Published In: | Volume 7 Issue 5, May-2022 |
| DOI: | |
| Abstract: | A digital twin is a technology which represents real-life objects or devices virtually . It is similar to 3D renderings of computer-aided design (CAD) models. But the main difference between digital twins differ and simple 3D models is that, digital twin technology also combines the physical elements and the dynamics of how that object or device operates in the real world. In other words, we can see, almost in real time, precisely how an object or device responds throughout its lifecycle. Just as an asset moves in response to factors such as climate, ambient temperature, user idiosyncrasies and so on, so does its digital twin. Digital twins do this by combining data collected from sensors on the device, with knowledge related to the design, build, operation and servicing of the physical twin. Already, just from this data, we can have a rich, highly detailed picture of the asset. Intelligence, in the form of mathematics, physics, and machine learning and then building on data, has acted as a 'brain' of digital twin technology and performs things like model prediction, development and early warning systems happen. Multiple forms of digital transformation are imminent. Digital Twins represent one concept. It grows because it can give real visibility. The rapid spread of digital twin is facing obstacles due to the lack of semantic interaction between structures, levels and ontologies. The technology required for automatic detection is lacking. The continuity of the forum depends on the combination of information technology, operational and communication technology with protocol-agnostic. Making sense of the data, ability to curate data and perform data analytics at the edge is key to value. Delivering engines to the edge are crucial for analytics at the edge when latency is critical. The combination of these and other factors may chart the future path of Digital Twins. The amount of unknown unknowns and the known unknowns in this process makes it imperative to create global infrastructures and organize groups to pursue infrastructure development blocks and new ideas through research. |
| Keywords: | Digital Twin, Digital Twin Data, DTD |
| Cite Article: | "UNDERSTANDING THE APPLICATION OF DIGITAL TWIN TECHNOLOGY IN DIFFERENT FIELDS", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 5, page no.1024-1028, May-2022, Available :http://www.ijnrd.org/papers/IJNRD2205124.pdf |
| Downloads: | 000118762 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID:IJNRD2205124 Registration ID: 181502 Published In: Volume 7 Issue 5, May-2022 DOI (Digital Object Identifier): Page No: 1024-1028 Country: Palakkad, Kerala, India Research Area: Science Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2205124 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2205124 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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