{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T13:45:39Z","timestamp":1785246339300,"version":"3.55.0"},"reference-count":83,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2023,11,2]],"date-time":"2023-11-02T00:00:00Z","timestamp":1698883200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,2]],"date-time":"2023-11-02T00:00:00Z","timestamp":1698883200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-17516-x","type":"journal-article","created":{"date-parts":[[2023,11,2]],"date-time":"2023-11-02T05:13:34Z","timestamp":1698902014000},"page":"49567-49594","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Environment awareness, multimodal interaction, and intelligent assistance in industrial augmented reality solutions with deep learning"],"prefix":"10.1007","volume":"83","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0076-7001","authenticated-orcid":false,"given":"Juan","family":"Izquierdo-Domenech","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jordi","family":"Linares-Pellicer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isabel","family":"Ferri-Molla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,11,2]]},"reference":[{"key":"17516_CR1","doi-asserted-by":"crossref","unstructured":"Kagermann H, Helbig J, Hellinger A, Wahlster W (2013) Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Securing the future of German manufacturing industry; final report of the Industrie 4.0 Working Group (Forschungsunion, 2013)","DOI":"10.3390\/sci4030026"},{"issue":"8","key":"17516_CR2","doi-asserted-by":"publisher","first-page":"2941","DOI":"10.1080\/00207543.2018.1444806","volume":"56","author":"LD Xu","year":"2018","unstructured":"Xu LD, Xu EL, Li L (2018) Industry 4.0: State of the art and future trends. Int J Prod Res 56(8):2941\u20132962. https:\/\/doi.org\/10.1080\/00207543.2018.1444806","journal-title":"Int J Prod Res"},{"key":"17516_CR3","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1016\/j.jmsy.2021.05.006","volume":"61","author":"CH Chu","year":"2021","unstructured":"Chu CH, Wang L, Liu S, Zhang Y, Menozzi M (2021) Augmented reality in smart manufacturing: Enabling collaboration between humans and artificial intelligence. J Manuf Syst 61:658\u2013659. https:\/\/doi.org\/10.1016\/j.jmsy.2021.05.006","journal-title":"J Manuf Syst"},{"key":"17516_CR4","doi-asserted-by":"crossref","unstructured":"Guerreiro BV, Lins RG, Sun J, Schmitt R (2018) In Advances in manufacturing, vol 0 (Springer Heidelberg 2018) pp 161\u2013170. 10.1007\/978-3-319-68619-6_16","DOI":"10.1007\/978-3-319-68619-6_16"},{"key":"17516_CR5","doi-asserted-by":"publisher","unstructured":"Runji JM, Lee YJ, Chu CH (2022) Systematic literature review on augmented reality-based maintenance applications in manufacturing centered on operator needs. Int J Precision Eng Manufacturing-Green Technol. https:\/\/doi.org\/10.1007\/s40684-022-00444-w","DOI":"10.1007\/s40684-022-00444-w"},{"key":"17516_CR6","volume-title":"A m\u00e1quina que mudou o mundo","author":"JP Womack","year":"1992","unstructured":"Womack JP, Jones DT, Roos D (1992) A m\u00e1quina que mudou o mundo. Campus, Rio de Janeiro"},{"issue":"1","key":"17516_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s40436-015-0131-4","volume":"4","author":"X Wang","year":"2016","unstructured":"Wang X, Ong SK, Nee AY (2016) A comprehensive survey of augmented reality assembly research. Advances in Manufacturing 4(1):1\u201322. https:\/\/doi.org\/10.1007\/s40436-015-0131-4","journal-title":"Advances in Manufacturing"},{"key":"17516_CR8","doi-asserted-by":"publisher","unstructured":"Zonta T, da\u00a0Costa CA, da\u00a0Rosa\u00a0Righi R, de\u00a0Lima MJ, da\u00a0Trindade ES, Li GP (2020) Predictive maintenance in the Industry 4.0: A systematic literature review. Computers and Industrial Engineering 150. https:\/\/doi.org\/10.1016\/j.cie.2020.106889","DOI":"10.1016\/j.cie.2020.106889"},{"key":"17516_CR9","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1016\/j.rcim.2017.06.002","volume":"49","author":"R Palmarini","year":"2018","unstructured":"Palmarini R, Erkoyuncu JA, Roy R, Torabmostaedi H (2018) A systematic review of augmented reality applications in maintenance. Robot Comput -Integr Manuf 49:215\u2013228. https:\/\/doi.org\/10.1016\/j.rcim.2017.06.002","journal-title":"Robot Comput -Integr Manuf"},{"key":"17516_CR10","unstructured":"Jaschke S (2014) In Proceedings of 2014 international conference on interactive collaborative learning, ICL 2014 (Institute of Electrical and Electronics Engineers Inc., 2014), pp. 605\u2013608. 10.1109\/ICL.2014.7017840"},{"issue":"4","key":"17516_CR11","doi-asserted-by":"publisher","first-page":"20","DOI":"10.3991\/ijim.v8i4.3797","volume":"8","author":"AM Huenerfauth","year":"2014","unstructured":"Huenerfauth AM (2014) Mobile technology applications for manufacturing, reduction of muda (waste) and the effect on manufacturing economy and efficiency. Int J Interactive Mobile Technol 8(4):20\u201323. https:\/\/doi.org\/10.3991\/ijim.v8i4.3797","journal-title":"Int J Interactive Mobile Technol"},{"issue":"3\u20134","key":"17516_CR12","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1007\/s11740-021-01026-6","volume":"15","author":"C Kollatsch","year":"2021","unstructured":"Kollatsch C, Klimant P (2021) Efficient integration process of production data into Augmented Reality based maintenance of machine tools. Prod Eng Res Devel 15(3\u20134):311\u2013319. https:\/\/doi.org\/10.1007\/s11740-021-01026-6","journal-title":"Prod Eng Res Devel"},{"key":"17516_CR13","doi-asserted-by":"crossref","unstructured":"Gattullo M, Scurati GW, Fiorentino M, Uva AE, Ferrise F, Bordegoni M (2019) Towards augmented reality manuals for industry 4.0: A methodology. Robot Comput -Integr Manuf 56(March 2018):276\u2013286. 10.1016\/j.rcim.2018.10.001","DOI":"10.1016\/j.rcim.2018.10.001"},{"key":"17516_CR14","doi-asserted-by":"crossref","unstructured":"Gilchrist A (2016) In Industry 4.0 (Springer, 2016) chap\u00a013, pp 195\u2013215. 10.1007\/978-1-4842-2047-4","DOI":"10.1007\/978-1-4842-2047-4_13"},{"key":"17516_CR15","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/0167-8760(94)90042-6","volume":"16","author":"RW Backs","year":"1994","unstructured":"Backs RW, Seljos KA (1994) Metabolic and cardiorespiratory measures of mental effort: the effects of level of difficulty in a working memory task. Int J Psychophysiol 16:57\u201368","journal-title":"Int J Psychophysiol"},{"issue":"2","key":"17516_CR16","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1207\/s15516709cog1202_4","volume":"12","author":"J Sweller","year":"1988","unstructured":"Sweller J (1988) Cognitive Load During Problem Solving: Effects on Learning. Cogn Sci 12(2):257\u2013285. https:\/\/doi.org\/10.1207\/s15516709cog1202_4","journal-title":"Cogn Sci"},{"issue":"3","key":"17516_CR17","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1002\/wcs.1222","volume":"4","author":"C Sandi","year":"2013","unstructured":"Sandi C (2013) Stress and cognition. Wiley Interdisciplinary Rev: Cogn Sci 4(3):245\u2013261. https:\/\/doi.org\/10.1002\/wcs.1222","journal-title":"Wiley Interdisciplinary Rev: Cogn Sci"},{"key":"17516_CR18","doi-asserted-by":"publisher","unstructured":"Romero D, Stahre J, Taisch M (2020) The Operator 4.0: Towards socially sustainable factories of the future. https:\/\/doi.org\/10.1016\/j.cie.2019.106128","DOI":"10.1016\/j.cie.2019.106128"},{"key":"17516_CR19","unstructured":"Romero D, Stahre J, Wuest T, Noran O, Bernus P, Fast-Berglund A, Gorecky D (2016) In Proceedings of the international conference on computers and industrial engineering (CIE46) (Tianjin, China 2016), pp 29\u201331. https:\/\/www.researchgate.net\/publication\/309609488"},{"key":"17516_CR20","doi-asserted-by":"publisher","unstructured":"Peruzzini M, Grandi F, Pellicciari M (2020) Exploring the potential of Operator 4.0 interface and monitoring. Computers and Industrial Engineering 139. https:\/\/doi.org\/10.1016\/j.cie.2018.12.047","DOI":"10.1016\/j.cie.2018.12.047"},{"key":"17516_CR21","doi-asserted-by":"crossref","unstructured":"Zambiasi LP, Rabelo RJ, Zambiasi SP, Lizot R (2022) In IFIP international conference on advances in production management systems pp 494\u2013502. https:\/\/link.springer.com\/bookseries\/6102","DOI":"10.1007\/978-3-031-16411-8_57"},{"key":"17516_CR22","doi-asserted-by":"publisher","first-page":"1089","DOI":"10.1016\/j.procir.2021.11.183","volume":"104","author":"D Romero","year":"2021","unstructured":"Romero D, Stahre J (2021) Towards the resilient operator 5.0: the future of work in smart resilient manufacturing systems. Procedia CIRP 104:1089\u20131094. https:\/\/doi.org\/10.1016\/j.procir.2021.11.183","journal-title":"Procedia CIRP"},{"key":"17516_CR23","doi-asserted-by":"publisher","unstructured":"Rabelo RJ, Romero D, Popov\u00a0Zambiasi S (2018) In IFIP international conference on advances in production management systems (APMS), pp 456\u2013464. https:\/\/doi.org\/10.1007\/978-3-319-99707-0_57, https:\/\/inria.hal.science\/hal-02177873","DOI":"10.1007\/978-3-319-99707-0_57"},{"key":"17516_CR24","volume-title":"ISODATA, a novel method of data analysis and pattern classification","author":"GH Ball","year":"1965","unstructured":"Ball GH, Hall DJ (1965) ISODATA, a novel method of data analysis and pattern classification. Tech. rep, Stanford research inst Menlo Park CA"},{"key":"17516_CR25","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/BF00994018","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes C, Vapnik V, Saitta L (1995) Support-Vector Networks Editor. Mach Learn 20:273\u2013297","journal-title":"Mach Learn"},{"key":"17516_CR26","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) In Advances in neural information processing systems, vol\u00a030, pp 6000\u20136010. 10.48550\/arXiv.1706.03762"},{"key":"17516_CR27","doi-asserted-by":"publisher","unstructured":"Bommasani R, Hudson DA, Adeli E, Altman R, Arora S, von Arx S (2021) On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258, https:\/\/doi.org\/10.48550\/arXiv.2108.07258","DOI":"10.48550\/arXiv.2108.07258"},{"key":"17516_CR28","doi-asserted-by":"publisher","unstructured":"Rasmussen T, Feuchtner T, Huang W, Gr\u00f8nb\u00e6k K (2022) Supporting workspace awareness in remote assistance through a flexible multi-camera system and Augmented Reality awareness cues. J Vis Commun Image Represent 103655. https:\/\/doi.org\/10.1016\/J.JVCIR.2022.103655","DOI":"10.1016\/J.JVCIR.2022.103655"},{"key":"17516_CR29","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/J.MFGLET.2022.09.003","volume":"34","author":"L Eversberg","year":"2022","unstructured":"Eversberg L, Ebrahimi P, Pape M, Lambrecht J (2022) A cognitive assistance system with augmented reality for manual repair tasks with high variability based on the digital twin. Manufacturing Letters 34:49\u201352. https:\/\/doi.org\/10.1016\/J.MFGLET.2022.09.003","journal-title":"Manufacturing Letters"},{"key":"17516_CR30","doi-asserted-by":"publisher","unstructured":"Wang Z, Bai X, Zhang S, Billinghurst M, He W, Wang Y, Han D, Chen G, Li J (2021) The role of user-centered AR instruction in improving novice spatial cognition in a high-precision procedural task. Adv Eng Inform 47. https:\/\/doi.org\/10.1016\/j.aei.2021.101250","DOI":"10.1016\/j.aei.2021.101250"},{"key":"17516_CR31","doi-asserted-by":"publisher","unstructured":"Zhang J, Wang S, He W, Li J, Cao Z, Wei B (2022) Projected augmented reality assembly assistance system supporting multi-modal interaction. Int J Adv Manufact Technol 2022 123:3 123(3):1353\u20131367. https:\/\/doi.org\/10.1007\/S00170-022-10113-6","DOI":"10.1007\/S00170-022-10113-6"},{"key":"17516_CR32","doi-asserted-by":"crossref","unstructured":"Sheu PCy (2010) Semantic computing (Wiley Online Library, 2010)","DOI":"10.1002\/9780470588222"},{"issue":"16","key":"17516_CR33","doi-asserted-by":"publisher","first-page":"4903","DOI":"10.1080\/00207543.2020.1859636","volume":"59","author":"CK Sahu","year":"2021","unstructured":"Sahu CK, Young C, Rai R (2021) Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review. Int J Prod Res 59(16):4903\u20134959. https:\/\/doi.org\/10.1080\/00207543.2020.1859636","journal-title":"Int J Prod Res"},{"issue":"114","key":"17516_CR34","doi-asserted-by":"publisher","first-page":"820","DOI":"10.1016\/J.ESWA.2021.114820","volume":"175","author":"M Bertolini","year":"2021","unstructured":"Bertolini M, Mezzogori D, Neroni M, Zammori F (2021) Machine Learning for industrial applications: A comprehensive literature review. Expert Syst Appl 175(114):820. https:\/\/doi.org\/10.1016\/J.ESWA.2021.114820","journal-title":"Expert Syst Appl"},{"issue":"8","key":"17516_CR35","doi-asserted-by":"publisher","first-page":"11,240","DOI":"10.1016\/J.ESWA.2009.02.073","volume":"36","author":"H Esen","year":"2009","unstructured":"Esen H, Ozgen F, Esen M, Sengur A (2009) Artificial neural network and wavelet neural network approaches for modelling of a solar air heater. Expert Syst Appl 36(8):11,240-11,248. https:\/\/doi.org\/10.1016\/J.ESWA.2009.02.073","journal-title":"Expert Syst Appl"},{"key":"17516_CR36","doi-asserted-by":"publisher","unstructured":"Zamora-Hern\u00e1ndez MA, Castro-Vargas JA, Azorin-Lopez J, Garcia-Rodriguez J (2021) Deep learning-based visual control assistant for assembly in Industry 4.0. Computers in Industry https:\/\/doi.org\/10.1016\/j.compind.2021.103485","DOI":"10.1016\/j.compind.2021.103485"},{"key":"17516_CR37","doi-asserted-by":"publisher","unstructured":"Javaid AY, Niyaz Q, Sun W, Alam M (2015) A deep learning approach for network intrusion detection system. EAI International Conference on Bio-inspired Information and Communications Technologies (BICT). https:\/\/doi.org\/10.4108\/eai.3-12-2015.2262516","DOI":"10.4108\/eai.3-12-2015.2262516"},{"key":"17516_CR38","doi-asserted-by":"publisher","unstructured":"Chalapathy R, Chawla S (2019) Deep Learning for Anomaly Detection: A Survey pp 1\u201350. arXiv preprint arXiv:1901.03407, https:\/\/doi.org\/10.48550\/arXiv.1901.03407","DOI":"10.48550\/arXiv.1901.03407"},{"key":"17516_CR39","unstructured":"Ionescu RT, Khan FS, Georgescu MI, Shao L (2019) In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 7842\u20137851"},{"issue":"9","key":"17516_CR40","doi-asserted-by":"publisher","first-page":"4321","DOI":"10.1109\/TIP.2017.2713048","volume":"26","author":"W Lu","year":"2017","unstructured":"Lu W, Cheng Y, Xiao C, Chang S, Huang S, Liang B, Huang T (2017) Unsupervised sequential outlier detection with deep architectures. IEEE Trans Image Process 26(9):4321\u20134330. https:\/\/doi.org\/10.1109\/TIP.2017.2713048","journal-title":"IEEE Trans Image Process"},{"key":"17516_CR41","unstructured":"Pang G, Yan C, Shen C, Van Den\u00a0Hengel A, Bai X (2020) In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 12,173\u201312,182"},{"key":"17516_CR42","doi-asserted-by":"publisher","unstructured":"Zenati H, Foo CS, Lecouat B, Manek G, Chandrasekhar VR (2018) Efficient GAN-based anomaly detection. arXiv preprint arXiv:1802.06222, https:\/\/doi.org\/10.48550\/arXiv.1802.06222","DOI":"10.48550\/arXiv.1802.06222"},{"key":"17516_CR43","doi-asserted-by":"publisher","unstructured":"\u0160kv\u00e1ra V, Pevn\u00fd T, \u0160m\u00eddl V (2018) Are generative deep models for novelty detection truly better? arXiv preprint arXiv:1807.05027, https:\/\/doi.org\/10.48550\/arXiv.1807.05027","DOI":"10.48550\/arXiv.1807.05027"},{"issue":"9","key":"17516_CR44","doi-asserted-by":"publisher","first-page":"4138","DOI":"10.1016\/J.JFRANKLIN.2022.04.003","volume":"359","author":"X Song","year":"2022","unstructured":"Song X, Sun P, Song S, Stojanovic V (2022) Event-driven NN adaptive fixed-time control for nonlinear systems with guaranteed performance. J Franklin Inst 359(9):4138\u20134159. https:\/\/doi.org\/10.1016\/J.JFRANKLIN.2022.04.003","journal-title":"J Franklin Inst"},{"issue":"2","key":"17516_CR45","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1016\/J.IFACOL.2020.12.126","volume":"53","author":"RB Gopaluni","year":"2020","unstructured":"Gopaluni RB, Tulsyan A, Chachuat B, Huang B, Lee JM, Amjad F, Damarla SK, Woo Kim J, Lawrence NP (2020) Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey. IFAC-PapersOnLine 53(2):218\u2013229. https:\/\/doi.org\/10.1016\/J.IFACOL.2020.12.126","journal-title":"IFAC-PapersOnLine"},{"issue":"5","key":"17516_CR46","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1080\/10447318.2014.994194","volume":"31","author":"R Radkowski","year":"2015","unstructured":"Radkowski R, Herrema J, Oliver J (2015) Augmented reality-based manual assembly support with visual features for different degrees of difficulty. Int J Human-Comput Inter 31(5):337\u2013349. https:\/\/doi.org\/10.1080\/10447318.2014.994194","journal-title":"Int J Human-Comput Inter"},{"key":"17516_CR47","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.compind.2018.02.001","volume":"98","author":"GW Scurati","year":"2018","unstructured":"Scurati GW, Gattullo M, Fiorentino M, Ferrise F, Bordegoni M, Uva AE (2018) Converting maintenance actions into standard symbols for Augmented Reality applications in Industry 4.0. Comput Ind 98:68\u201379. https:\/\/doi.org\/10.1016\/j.compind.2018.02.001","journal-title":"Comput Ind"},{"issue":"5","key":"17516_CR48","doi-asserted-by":"publisher","first-page":"905","DOI":"10.1007\/s10845-012-0642-9","volume":"24","author":"YP Luh","year":"2013","unstructured":"Luh YP, Wang JB, Chang JW, Chang SY, Chu CH (2013) Augmented reality-based design customization of footwear for children. J Intell Manuf 24(5):905\u2013917. https:\/\/doi.org\/10.1007\/s10845-012-0642-9","journal-title":"J Intell Manuf"},{"issue":"2","key":"17516_CR49","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1016\/j.destud.2009.11.001","volume":"31","author":"Y Shen","year":"2010","unstructured":"Shen Y, Ong SK, Nee AY (2010) Augmented reality for collaborative product design and development. Des Stud 31(2):118\u2013145. https:\/\/doi.org\/10.1016\/j.destud.2009.11.001","journal-title":"Des Stud"},{"issue":"1","key":"17516_CR50","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/j.cirp.2009.03.020","volume":"58","author":"SK Ong","year":"2009","unstructured":"Ong SK, Shen Y (2009) A mixed reality environment for collaborative product design and development. CIRP Ann Manuf Technol 58(1):139\u2013142. https:\/\/doi.org\/10.1016\/j.cirp.2009.03.020","journal-title":"CIRP Ann Manuf Technol"},{"issue":"1","key":"17516_CR51","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cirp.2011.03.001","volume":"60","author":"SK Ong","year":"2011","unstructured":"Ong SK, Wang ZB (2011) Augmented assembly technologies based on 3D bare-hand interaction. CIRP Ann Manuf Technol 60(1):1\u20134. https:\/\/doi.org\/10.1016\/j.cirp.2011.03.001","journal-title":"CIRP Ann Manuf Technol"},{"issue":"7","key":"17516_CR52","doi-asserted-by":"publisher","first-page":"1745","DOI":"10.1080\/00207540600972935","volume":"46","author":"ML Yuan","year":"2008","unstructured":"Yuan ML, Ong SK, Nee AY (2008) Augmented reality for assembly guidance using a virtual interactive tool. Int J Prod Res 46(7):1745\u20131767. https:\/\/doi.org\/10.1080\/00207540600972935","journal-title":"Int J Prod Res"},{"key":"17516_CR53","doi-asserted-by":"publisher","unstructured":"Mourtzis D, Siatras V, Angelopoulos J (2020) Real-time remote maintenance support based on augmented reality (AR). Applied Sci (Switzerland) 10(5). https:\/\/doi.org\/10.3390\/app10051855","DOI":"10.3390\/app10051855"},{"key":"17516_CR54","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.compind.2016.11.004","volume":"85","author":"D Tati\u0107","year":"2017","unstructured":"Tati\u0107 D, Te\u0161i\u0107 B (2017) The application of augmented reality technologies for the improvement of occupational safety in an industrial environment. Comput Ind 85:1\u201310. https:\/\/doi.org\/10.1016\/j.compind.2016.11.004","journal-title":"Comput Ind"},{"issue":"4","key":"17516_CR55","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1016\/j.compind.2013.01.002","volume":"64","author":"DB Esp\u00edndola","year":"2013","unstructured":"Esp\u00edndola DB, Fumagalli L, Garetti M, Pereira CE, Botelho SS, Ventura Henriques R (2013) A model-based approach for data integration to improve maintenance management by mixed reality. Comput Ind 64(4):376\u2013391. https:\/\/doi.org\/10.1016\/j.compind.2013.01.002","journal-title":"Comput Ind"},{"key":"17516_CR56","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1016\/j.procs.2013.11.019","volume":"25","author":"LE Garza","year":"2013","unstructured":"Garza LE, Pantoja G, Ram\u00edrez P, Ram\u00edrez H, Rodr\u00edguez N, Gonz\u00e1lez E, Quintal R, P\u00e9rez JA (2013) Augmented reality application for the maintenance of a flapper valve of a fuller-kynion type m pump. Procedia Comput Sci 25:154\u2013160. https:\/\/doi.org\/10.1016\/j.procs.2013.11.019","journal-title":"Procedia Comput Sci"},{"key":"17516_CR57","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1016\/j.renene.2012.12.043","volume":"55","author":"S Benbelkacem","year":"2013","unstructured":"Benbelkacem S, Belhocine M, Bellarbi A, Zenati-Henda N, Tadjine M (2013) Augmented reality for photovoltaic pumping systems maintenance tasks. Renewable Energy 55:428\u2013437. https:\/\/doi.org\/10.1016\/j.renene.2012.12.043","journal-title":"Renewable Energy"},{"issue":"9\u201311","key":"17516_CR58","doi-asserted-by":"publisher","first-page":"2033","DOI":"10.1016\/j.fusengdes.2010.12.082","volume":"86","author":"Z Ziaei","year":"2011","unstructured":"Ziaei Z, Hahto A, Mattila J, Siuko M, Semeraro L (2011) Real-time markerless augmented reality for remote handling system in bad viewing conditions. Fusion Eng Des 86(9\u201311):2033\u20132038. https:\/\/doi.org\/10.1016\/j.fusengdes.2010.12.082","journal-title":"Fusion Eng Des"},{"key":"17516_CR59","doi-asserted-by":"publisher","unstructured":"Zenati N, Zerhouni N (2004) Achour K. In Proceedings of the IEEE international conference on industrial technology 2:848\u2013852. https:\/\/doi.org\/10.1109\/icit.2004.1490185","DOI":"10.1109\/icit.2004.1490185"},{"key":"17516_CR60","doi-asserted-by":"publisher","unstructured":"Barakonyi I, Psik T, Schmalstieg D (2004) In ISMAR 2004: Proceedings of the Third IEEE and ACM international symposium on mixed and augmented reality, pp 141\u2013150. https:\/\/doi.org\/10.1109\/ISMAR.2004.11","DOI":"10.1109\/ISMAR.2004.11"},{"issue":"6","key":"17516_CR61","doi-asserted-by":"publisher","first-page":"967","DOI":"10.1002\/cae.21772","volume":"24","author":"A Monroy Reyes","year":"2016","unstructured":"Monroy Reyes A, Vergara Villegas OO, Miranda Boj\u00f3rquez E, Cruz S\u00e1nchez VG, Nandayapa M (2016) A mobile augmented reality system to support machinery operations in scholar environments. Comput Appl Eng Educ 24(6):967\u2013981. https:\/\/doi.org\/10.1002\/cae.21772","journal-title":"Comput Appl Eng Educ"},{"issue":"4","key":"17516_CR62","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1016\/j.robot.2012.09.013","volume":"61","author":"S Webel","year":"2013","unstructured":"Webel S, Bockholt U, Engelke T, Gavish N, Olbrich M, Preusche C (2013) An augmented reality training platform for assembly and maintenance skills. Robot Auton Syst 61(4):398\u2013403. https:\/\/doi.org\/10.1016\/j.robot.2012.09.013","journal-title":"Robot Auton Syst"},{"issue":"1","key":"17516_CR63","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1109\/MCG.2011.4","volume":"31","author":"F De Crescenzio","year":"2011","unstructured":"De Crescenzio F, Fantini M, Persiani F, Di Stefano L, Azzari P, Salti S (2011) Augmented reality for aircraft maintenance training and operations support. IEEE Comput Graphics Appl 31(1):96\u2013101. https:\/\/doi.org\/10.1109\/MCG.2011.4","journal-title":"IEEE Comput Graphics Appl"},{"issue":"3","key":"17516_CR64","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1080\/24725854.2018.1493244","volume":"51","author":"E Bottani","year":"2019","unstructured":"Bottani E, Vignali G (2019) Augmented reality technology in the manufacturing industry: A review of the last decade. IISE Transactions 51(3):284\u2013310. https:\/\/doi.org\/10.1080\/24725854.2018.1493244","journal-title":"IISE Transactions"},{"key":"17516_CR65","unstructured":"Baldauf M, B\u00f6sch R, Frei C, Hautle F, Jenny M (2018) In MobileHCI 2018 - beyond mobile: the next 20 Years - 20th international conference on human-computer interaction with mobile devices and services, conference proceedings adjunct (Association for Computing Machinery, Inc, 2018), pp 119\u2013126. 10.1145\/3236112.3236128"},{"key":"17516_CR66","doi-asserted-by":"publisher","unstructured":"Coli E, Melluso N, Fantoni G, Mazzei D (2020) Towards automatic building of human-machine conversational system to support maintenance processes. arXiv preprint arXiv:2005.06517, https:\/\/doi.org\/10.48550\/arXiv.2005.06517","DOI":"10.48550\/arXiv.2005.06517"},{"key":"17516_CR67","doi-asserted-by":"publisher","unstructured":"Casillo M, Colace F, Fabbri L, Lombardi M, Romano A, Santaniello D (2020) In Proceedings of 2020 IEEE international conference on teaching, assessment, and learning for engineering, TALE 2020 (Institute of Electrical and Electronics Engineers Inc, 2020), pp 371\u2013376. https:\/\/doi.org\/10.1109\/TALE48869.2020.9368339","DOI":"10.1109\/TALE48869.2020.9368339"},{"issue":"1","key":"17516_CR68","doi-asserted-by":"publisher","first-page":"499","DOI":"10.2478\/mape-2021-0045","volume":"4","author":"K Mleczko","year":"2021","unstructured":"Mleczko K (2021) Chatbot as a tool for knowledge sharing in the maintenance and repair processes. Multidisciplinary Aspects Prod Eng 4(1):499\u2013508. https:\/\/doi.org\/10.2478\/mape-2021-0045","journal-title":"Multidisciplinary Aspects Prod Eng"},{"key":"17516_CR69","unstructured":"TeamViewer (2021) TeamViewer Assist AR. www.teamviewer.com\/es\/realidad-aumentada"},{"key":"17516_CR70","unstructured":"PTC (2017) Vuforia Chalk. www.ptc.com\/es\/products\/vuforia\/vuforia-chalk"},{"key":"17516_CR71","unstructured":"Shneiderman B, Plaisant C, Cohen MS, Jacobs S, Elmqvist N, Diakopoulos N (2016) Designing the user interface: strategies for effective human-computer interaction (Pearson, 2016)"},{"key":"17516_CR72","unstructured":"Google (2018) ARCore. https:\/\/www.developers.google.com\/ar"},{"key":"17516_CR73","unstructured":"Apple (2017) ARKit. https:\/\/www.developer.apple.com\/augmented-reality"},{"key":"17516_CR74","unstructured":"Unity (2018) AR Foundation. https:\/\/www.unity.com\/es\/unity\/features\/arfoundation"},{"key":"17516_CR75","doi-asserted-by":"publisher","unstructured":"Kato H, Billinghurst M (1999) In Proceedings - 2nd IEEE and acm international workshop on augmented reality, IWAR 1999 (Institute of Electrical and Electronics Engineers Inc, 1999), pp 85\u201394. https:\/\/doi.org\/10.1109\/IWAR.1999.803809","DOI":"10.1109\/IWAR.1999.803809"},{"key":"17516_CR76","doi-asserted-by":"publisher","unstructured":"Liu Y, Ott M, Goyal N, Du J, Joshi M, Chen D, Levy O, Lewis M, Zettlemoyer L, Stoyanov V (2019) RoBERTa: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692, https:\/\/doi.org\/10.48550\/arXiv.1907.11692","DOI":"10.48550\/arXiv.1907.11692"},{"key":"17516_CR77","doi-asserted-by":"publisher","unstructured":"Sanh V, Debut L, Chaumond J, Wolf T (2019) DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. arXiv preprint arXiv:1910.01108, https:\/\/doi.org\/10.48550\/arXiv.1910.01108","DOI":"10.48550\/arXiv.1910.01108"},{"issue":"1","key":"17516_CR78","doi-asserted-by":"publisher","first-page":"5485","DOI":"10.48550\/arXiv.1910.10683","volume":"21","author":"C Raffel","year":"2020","unstructured":"Raffel C, Shazeer N, Roberts A, Lee K, Narang S, Matena M, Zhou Y, Li W, Liu PJ (2020) Exploring the limits of transfer learning with a unified text-to-text transformer. J Mach Learn Res 21(1):5485\u20135551. https:\/\/doi.org\/10.48550\/arXiv.1910.10683","journal-title":"J Mach Learn Res"},{"key":"17516_CR79","doi-asserted-by":"publisher","unstructured":"Rajpurkar P, Zhang J, Lopyrev K, Liang P (2016) SQuAD: 100,000+ Questions for machine comprehension of text. arXiv preprint arXiv:1606.05250, https:\/\/doi.org\/10.48550\/arXiv.1606.05250","DOI":"10.48550\/arXiv.1606.05250"},{"key":"17516_CR80","unstructured":"The Linux Foundation (2017) ONNX: open neural network exchange. https:\/\/www.github.com\/onnx"},{"key":"17516_CR81","unstructured":"Chollet F (2015) Keras. https:\/\/www.github.com\/fchollet\/keras"},{"key":"17516_CR82","doi-asserted-by":"publisher","unstructured":"Zafrir O, Larey A, Boudoukh G, Shen H, Wasserblat M (2021) Prune Once for All: sparse pre-trained language models. arXiv preprint arXiv:2111.05754, https:\/\/doi.org\/10.48550\/arXiv.2111.05754","DOI":"10.48550\/arXiv.2111.05754"},{"issue":"118","key":"17516_CR83","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1016\/J.ESWA.2022.118983","volume":"213","author":"M Eswaran","year":"2023","unstructured":"Eswaran M, Gulivindala AK, Inkulu AK, Raju Bahubalendruni M (2023) Augmented reality-based guidance in product assembly and maintenance\/repair perspective: A state of the art review on challenges and opportunities. Expert Syst Appl 213(118):983. https:\/\/doi.org\/10.1016\/J.ESWA.2022.118983","journal-title":"Expert Syst Appl"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17516-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-17516-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17516-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T11:35:09Z","timestamp":1715081709000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-17516-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,2]]},"references-count":83,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["17516"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-17516-x","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,2]]},"assertion":[{"value":"7 May 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 November 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflicts of interest to report regarding the present study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}]}}