A Cost-Effective Thermal Imaging Safety Sensor for Industry 5.0 and Collaborative Robotics

UDC.coleccionInvestigaciónes_ES
UDC.conferenceTitleEdge-IoT 2022- SmartGov 2022es_ES
UDC.departamentoEnxeñaría de Computadoreses_ES
UDC.endPage15es_ES
UDC.grupoInvGrupo de Tecnoloxía Electrónica e Comunicacións (GTEC)es_ES
UDC.journalTitleSmart Technologies for Sustainable and Resilient Ecosystemses_ES
UDC.startPage3es_ES
UDC.volume510es_ES
dc.contributor.authorBarros, Daniel
dc.contributor.authorFraga-Lamas, Paula
dc.contributor.authorFernández-Caramés, Tiago M.
dc.contributor.authorLopes, Sérgio Ivan
dc.date.accessioned2024-10-31T10:38:41Z
dc.date.available2024-10-31T10:38:41Z
dc.date.issued2023
dc.descriptionPresented at: 3rd International Conference on Intelligent Edge Processing in the IoT Era, Edge-IoT 2022, and the 4th International Conference on Smart Governance for Sustainable Smart Cities, SmartGov 2022 Virtual, Online, 16 November 2022 through 18 November 2022es_ES
dc.descriptionThis version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-35982-8_1es_ES
dc.description.abstract[Abstract]: The Industry 5.0 paradigm focuses on industrial operator well-being and sustainable manufacturing practices, where humans play a central role, not only during the repetitive and collaborative tasks of the manufacturing process, but also in the management of the factory floor assets. Human factors, such as ergonomics, safety, and well-being, push the human-centric smart factory to efficiently adopt novel technologies while minimizing environmental and social impact. As operations at the factory floor increasingly rely on collaborative robots (CoBots) and flexible manufacturing systems, there is a growing demand for redundant safety mechanisms (i.e., automatic human detection in the proximity of machinery that is under operation). Fostering enhanced process safety for human proximity detection allows for the protection against possible incidents or accidents with the deployed industrial devices and machinery. This paper introduces the design and implementation of a cost-effective thermal imaging Safety Sensor that can be used in the scope of Industry 5.0 to trigger distinct safe mode states in manufacturing processes that rely on collaborative robotics. The proposed Safety Sensor uses a hybrid detection approach and has been evaluated under controlled environmental conditions. The obtained results show a 97% accuracy at low computational cost when using the developed hybrid method to detect the presence of humans in thermal images.es_ES
dc.description.sponsorshipThis work is a result of the project TECH-Technology, Environment, Creativity and Health, Norte-01-0145-FEDER-000043, supported by Norte Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). P.F.L and T.M.F.C. have been supported by Centro de Investigación de Galicia “CITIC” for a three-month research stay in Instituto Politécnico de Viana do Castelo between 15 June and 15 September 2022. CITIC, as Research Center accredited by Galician University System, is funded by “Consellería de Cultura, Educación e Universidades from Xunta de Galicia”, supported in an 80% through ERDF Funds, ERDF Operational Programme Galicia 2014–2020, and the remaining 20% by “Secretaría Xeral de Universidades” (Grant ED431G 2019/01). In addition, this work has been funded by the Xunta de Galicia (by grant ED431C 2020/15), the Agencia Estatal de Investigación of Spain, MCIN/AEI/10.13039/501100011033 (by grant PID2020-118857RA-I00 (ORBALLO)) and ERDF funds of the EU (FEDER Galicia 2014-2020 & AEI/FEDER Programs, UE).es_ES
dc.description.sponsorshipPortugal. Comissão de Coordenação e Desenvolvimento Regional do Norte; Norte-01-0145-FEDER-000043es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2020/15es_ES
dc.identifier.citationBarros, D., Fraga-Lamas, P., Fernández-Caramés, T.M., Lopes, S.I. (2023). A Cost-Effective Thermal Imaging Safety Sensor for Industry 5.0 and Collaborative Robotics. In: Lopes, S.I., Fraga-Lamas, P., Fernández-Caramés, T.M., Dawadi, B.R., Rawat, D.B., Shakya, S. (eds) Smart Technologies for Sustainable and Resilient Ecosystems. Edge-IoT SmartGov 2022 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 510. Springer, Cham. https://doi.org/10.1007/978-3-031-35982-8_1es_ES
dc.identifier.doi10.1007/978-3-031-35982-8_1
dc.identifier.isbn9783031359811
dc.identifier.issn1867-8211
dc.identifier.urihttp://hdl.handle.net/2183/39905
dc.language.isoenges_ES
dc.publisherSpringer Science and Business Media Deutschland GmbHes_ES
dc.relation.ispartofseriesLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICSTes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-118857RA-100/ES/EDGE COMPUTING OPORTUNISTA BASADO EN DISPOSITIVOS LOT MÓVILES Y DE BAJA POTENCIA (ORBALLO)es_ES
dc.relation.urihttps://doi.org/10.1007/978-3-031-35982-8_1es_ES
dc.rights© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineeringes_ES
dc.rights.accessRightsopen accesses_ES
dc.subjectIndustry 5.0es_ES
dc.subjectSafetyes_ES
dc.subjectHuman-centrices_ES
dc.subjectThermal Imaginges_ES
dc.subjectCobotses_ES
dc.titleA Cost-Effective Thermal Imaging Safety Sensor for Industry 5.0 and Collaborative Roboticses_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
relation.isAuthorOfPublicationcaa923d2-cf88-405e-9025-759d06cf3799
relation.isAuthorOfPublication79dbfabd-7261-41ff-9667-2f774d5f341e
relation.isAuthorOfPublication.latestForDiscoverycaa923d2-cf88-405e-9025-759d06cf3799

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