The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities
<p dir="ltr">Digital twinning is one of the top ten technology trends in the last couple of years, due to its high applicability in the industrial sector. The integration of big data analytics and artificial intelligence/machine learning (AI-ML) techniques with digital twinning, furt...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| مؤلفون آخرون: | , , , |
| منشور في: |
2021
|
| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
| _version_ | 1864513560415043584 |
|---|---|
| author | M. Mazhar Rathore (16896399) |
| author2 | Syed Attique Shah (9371981) Dhirendra Shukla (16896402) Elmahdi Bentafat (16896405) Spiridon Bakiras (16896408) |
| author2_role | author author author author |
| author_facet | M. Mazhar Rathore (16896399) Syed Attique Shah (9371981) Dhirendra Shukla (16896402) Elmahdi Bentafat (16896405) Spiridon Bakiras (16896408) |
| author_role | author |
| dc.creator.none.fl_str_mv | M. Mazhar Rathore (16896399) Syed Attique Shah (9371981) Dhirendra Shukla (16896402) Elmahdi Bentafat (16896405) Spiridon Bakiras (16896408) |
| dc.date.none.fl_str_mv | 2021-02-22T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/access.2021.3060863 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/The_Role_of_AI_Machine_Learning_and_Big_Data_in_Digital_Twinning_A_Systematic_Literature_Review_Challenges_and_Opportunities/24049290 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Artificial intelligence Data management and data science Machine learning Big Data Digital twin Patents Industries Systematics Tools Libraries Artificial intelligence Machine learning Industry 4.0 |
| dc.title.none.fl_str_mv | The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Digital twinning is one of the top ten technology trends in the last couple of years, due to its high applicability in the industrial sector. The integration of big data analytics and artificial intelligence/machine learning (AI-ML) techniques with digital twinning, further enriches its significance and research potential with new opportunities and unique challenges. To date, a number of scientific models have been designed and implemented related to this evolving topic. However, there is no systematic review of digital twinning, particularly focusing on the role of AI-ML and big data, to guide the academia and industry towards future developments. Therefore, this article emphasizes the role of big data and AI-ML in the creation of digital twins (DTs) or DT-based systems for various industrial applications, by highlighting the current state-of-the-art deployments. We performed a systematic review on top of multidisciplinary electronic bibliographic databases, in addition to existing patents in the field. Also, we identified development-tools that can facilitate various levels of the digital twinning. Further, we designed a big data driven and AI-enriched reference architecture that leads developers to a complete DT-enabled system. Finally, we highlighted the research potential of AI-ML for digital twinning by unveiling challenges and current opportunities.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2021.3060863" target="_blank">https://dx.doi.org/10.1109/access.2021.3060863</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_c60404ce22014206cf280df87551b12c |
| identifier_str_mv | 10.1109/access.2021.3060863 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24049290 |
| publishDate | 2021 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and OpportunitiesM. Mazhar Rathore (16896399)Syed Attique Shah (9371981)Dhirendra Shukla (16896402)Elmahdi Bentafat (16896405)Spiridon Bakiras (16896408)Information and computing sciencesArtificial intelligenceData management and data scienceMachine learningBig DataDigital twinPatentsIndustriesSystematicsToolsLibrariesArtificial intelligenceMachine learningIndustry 4.0<p dir="ltr">Digital twinning is one of the top ten technology trends in the last couple of years, due to its high applicability in the industrial sector. The integration of big data analytics and artificial intelligence/machine learning (AI-ML) techniques with digital twinning, further enriches its significance and research potential with new opportunities and unique challenges. To date, a number of scientific models have been designed and implemented related to this evolving topic. However, there is no systematic review of digital twinning, particularly focusing on the role of AI-ML and big data, to guide the academia and industry towards future developments. Therefore, this article emphasizes the role of big data and AI-ML in the creation of digital twins (DTs) or DT-based systems for various industrial applications, by highlighting the current state-of-the-art deployments. We performed a systematic review on top of multidisciplinary electronic bibliographic databases, in addition to existing patents in the field. Also, we identified development-tools that can facilitate various levels of the digital twinning. Further, we designed a big data driven and AI-enriched reference architecture that leads developers to a complete DT-enabled system. Finally, we highlighted the research potential of AI-ML for digital twinning by unveiling challenges and current opportunities.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2021.3060863" target="_blank">https://dx.doi.org/10.1109/access.2021.3060863</a></p>2021-02-22T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2021.3060863https://figshare.com/articles/journal_contribution/The_Role_of_AI_Machine_Learning_and_Big_Data_in_Digital_Twinning_A_Systematic_Literature_Review_Challenges_and_Opportunities/24049290CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/240492902021-02-22T00:00:00Z |
| spellingShingle | The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities M. Mazhar Rathore (16896399) Information and computing sciences Artificial intelligence Data management and data science Machine learning Big Data Digital twin Patents Industries Systematics Tools Libraries Artificial intelligence Machine learning Industry 4.0 |
| status_str | publishedVersion |
| title | The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities |
| title_full | The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities |
| title_fullStr | The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities |
| title_full_unstemmed | The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities |
| title_short | The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities |
| title_sort | The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities |
| topic | Information and computing sciences Artificial intelligence Data management and data science Machine learning Big Data Digital twin Patents Industries Systematics Tools Libraries Artificial intelligence Machine learning Industry 4.0 |