ARTiCO - AR in Tissue Converting - PERCOM 2022, Demo Session ...
For fully up-taking the advances achieved in pervasive monitoring systems within Industry 4.0, novel intelligent interfaces are needed to ease interactions with human personnel and enable them to access the available data and services ergonomically. To this end, we present a mobile app based on augm...
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Format: | Text |
Language: | English |
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Zenodo
2022
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Online Access: | https://dx.doi.org/10.5281/zenodo.7717076 https://zenodo.org/record/7717076 |
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author | Moroni, Davide Pieri, Gabriele Tampucci, Marco Masini, Daniele |
author_facet | Moroni, Davide Pieri, Gabriele Tampucci, Marco Masini, Daniele |
author_sort | Moroni, Davide |
collection | DataCite |
description | For fully up-taking the advances achieved in pervasive monitoring systems within Industry 4.0, novel intelligent interfaces are needed to ease interactions with human personnel and enable them to access the available data and services ergonomically. To this end, we present a mobile app based on augmented reality that allows operators to receive location-aware notifications and access and visualize real-time information and guidance for troubleshooting and plant maintenance. The app has been tailored to respond to the needs of a specific scenario, i.e. tissue converting, where it has provided encouraging results. ... |
format | Text |
genre | artico |
genre_facet | artico |
id | ftdatacite:10.5281/zenodo.7717076 |
institution | Open Polar |
language | English |
op_collection_id | ftdatacite |
op_doi | https://doi.org/10.5281/zenodo.771707610.5281/zenodo.7717077 |
op_relation | https://dx.doi.org/10.5281/zenodo.7717077 |
op_rights | Closed Access info:eu-repo/semantics/closedAccess |
publishDate | 2022 |
publisher | Zenodo |
record_format | openpolar |
spelling | ftdatacite:10.5281/zenodo.7717076 2025-01-16T20:56:23+00:00 ARTiCO - AR in Tissue Converting - PERCOM 2022, Demo Session ... Moroni, Davide Pieri, Gabriele Tampucci, Marco Masini, Daniele 2022 https://dx.doi.org/10.5281/zenodo.7717076 https://zenodo.org/record/7717076 en eng Zenodo https://dx.doi.org/10.5281/zenodo.7717077 Closed Access info:eu-repo/semantics/closedAccess Augmented reality Mobile app Predictive maintenance Pervasive vision Smart cameras Tissue converting Industry 4.0 Text ScholarlyArticle article-journal Presentation 2022 ftdatacite https://doi.org/10.5281/zenodo.771707610.5281/zenodo.7717077 2023-04-03T13:09:55Z For fully up-taking the advances achieved in pervasive monitoring systems within Industry 4.0, novel intelligent interfaces are needed to ease interactions with human personnel and enable them to access the available data and services ergonomically. To this end, we present a mobile app based on augmented reality that allows operators to receive location-aware notifications and access and visualize real-time information and guidance for troubleshooting and plant maintenance. The app has been tailored to respond to the needs of a specific scenario, i.e. tissue converting, where it has provided encouraging results. ... Text artico DataCite |
spellingShingle | Augmented reality Mobile app Predictive maintenance Pervasive vision Smart cameras Tissue converting Industry 4.0 Moroni, Davide Pieri, Gabriele Tampucci, Marco Masini, Daniele ARTiCO - AR in Tissue Converting - PERCOM 2022, Demo Session ... |
title | ARTiCO - AR in Tissue Converting - PERCOM 2022, Demo Session ... |
title_full | ARTiCO - AR in Tissue Converting - PERCOM 2022, Demo Session ... |
title_fullStr | ARTiCO - AR in Tissue Converting - PERCOM 2022, Demo Session ... |
title_full_unstemmed | ARTiCO - AR in Tissue Converting - PERCOM 2022, Demo Session ... |
title_short | ARTiCO - AR in Tissue Converting - PERCOM 2022, Demo Session ... |
title_sort | artico - ar in tissue converting - percom 2022, demo session ... |
topic | Augmented reality Mobile app Predictive maintenance Pervasive vision Smart cameras Tissue converting Industry 4.0 |
topic_facet | Augmented reality Mobile app Predictive maintenance Pervasive vision Smart cameras Tissue converting Industry 4.0 |
url | https://dx.doi.org/10.5281/zenodo.7717076 https://zenodo.org/record/7717076 |