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Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self‐Powered Sensor Enhanced Soft Robotic Manipulator
Rapid advancements of artificial intelligence of things (AIoT) technology pave the way for developing a digital‐twin‐based remote interactive system for advanced robotic‐enabled industrial automation and virtual shopping. The embedded multifunctional perception system is urged for better interaction...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292889/ https://www.ncbi.nlm.nih.gov/pubmed/34037331 http://dx.doi.org/10.1002/advs.202100230 |
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author | Sun, Zhongda Zhu, Minglu Zhang, Zixuan Chen, Zhaocong Shi, Qiongfeng Shan, Xuechuan Yeow, Raye Chen Hua Lee, Chengkuo |
author_facet | Sun, Zhongda Zhu, Minglu Zhang, Zixuan Chen, Zhaocong Shi, Qiongfeng Shan, Xuechuan Yeow, Raye Chen Hua Lee, Chengkuo |
author_sort | Sun, Zhongda |
collection | PubMed |
description | Rapid advancements of artificial intelligence of things (AIoT) technology pave the way for developing a digital‐twin‐based remote interactive system for advanced robotic‐enabled industrial automation and virtual shopping. The embedded multifunctional perception system is urged for better interaction and user experience. To realize such a system, a smart soft robotic manipulator is presented that consists of a triboelectric nanogenerator tactile (T‐TENG) and length (L‐TENG) sensor, as well as a poly(vinylidene fluoride) (PVDF) pyroelectric temperature sensor. With the aid of machine learning (ML) for data processing, the fusion of the T‐TENG and L‐TENG sensors can realize the automatic recognition of the grasped objects with the accuracy of 97.143% for 28 different shapes of objects, while the temperature distribution can also be obtained through the pyroelectric sensor. By leveraging the IoT and artificial intelligence (AI) analytics, a digital‐twin‐based virtual shop is successfully implemented to provide the users with real‐time feedback about the details of the product. In general, by offering a more immersive experience in human–machine interactions, the proposed remote interactive system shows the great potential of being the advanced human–machine interface for the applications of the unmanned working space. |
format | Online Article Text |
id | pubmed-8292889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82928892021-07-22 Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self‐Powered Sensor Enhanced Soft Robotic Manipulator Sun, Zhongda Zhu, Minglu Zhang, Zixuan Chen, Zhaocong Shi, Qiongfeng Shan, Xuechuan Yeow, Raye Chen Hua Lee, Chengkuo Adv Sci (Weinh) Research Articles Rapid advancements of artificial intelligence of things (AIoT) technology pave the way for developing a digital‐twin‐based remote interactive system for advanced robotic‐enabled industrial automation and virtual shopping. The embedded multifunctional perception system is urged for better interaction and user experience. To realize such a system, a smart soft robotic manipulator is presented that consists of a triboelectric nanogenerator tactile (T‐TENG) and length (L‐TENG) sensor, as well as a poly(vinylidene fluoride) (PVDF) pyroelectric temperature sensor. With the aid of machine learning (ML) for data processing, the fusion of the T‐TENG and L‐TENG sensors can realize the automatic recognition of the grasped objects with the accuracy of 97.143% for 28 different shapes of objects, while the temperature distribution can also be obtained through the pyroelectric sensor. By leveraging the IoT and artificial intelligence (AI) analytics, a digital‐twin‐based virtual shop is successfully implemented to provide the users with real‐time feedback about the details of the product. In general, by offering a more immersive experience in human–machine interactions, the proposed remote interactive system shows the great potential of being the advanced human–machine interface for the applications of the unmanned working space. John Wiley and Sons Inc. 2021-05-26 /pmc/articles/PMC8292889/ /pubmed/34037331 http://dx.doi.org/10.1002/advs.202100230 Text en © 2021 The Authors. Advanced Science published by Wiley‐VCH GmbH https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Sun, Zhongda Zhu, Minglu Zhang, Zixuan Chen, Zhaocong Shi, Qiongfeng Shan, Xuechuan Yeow, Raye Chen Hua Lee, Chengkuo Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self‐Powered Sensor Enhanced Soft Robotic Manipulator |
title | Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self‐Powered Sensor Enhanced Soft Robotic Manipulator |
title_full | Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self‐Powered Sensor Enhanced Soft Robotic Manipulator |
title_fullStr | Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self‐Powered Sensor Enhanced Soft Robotic Manipulator |
title_full_unstemmed | Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self‐Powered Sensor Enhanced Soft Robotic Manipulator |
title_short | Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self‐Powered Sensor Enhanced Soft Robotic Manipulator |
title_sort | artificial intelligence of things (aiot) enabled virtual shop applications using self‐powered sensor enhanced soft robotic manipulator |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292889/ https://www.ncbi.nlm.nih.gov/pubmed/34037331 http://dx.doi.org/10.1002/advs.202100230 |
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