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Human detector smart sensor for autonomous disinfection mobile robot

2021Conference paper Restricted access
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dc.contributor.authorMendonça, Hugo
dc.contributor.authorLima, José
dc.contributor.authorCosta, Paulo Gomes da
dc.contributor.authorMoreira, António Paulo G. M.
dc.contributor.authorSantos, Filipe Neves
dc.date.accessioned2022-04-05T08:35:18Z
dc.date.available2022-04-05T08:35:18Z
dc.date.issued2021
dc.description.abstractThe COVID-19 virus outbreak led to the need of developing smart disinfection systems, not only to protect the people that usually frequent public spaces but also to protect those who have to subject themselves to the contaminated areas. In this paper it is developed a human detector smart sensor for autonomous disinfection mobile robot that use Ultra Violet C type light for the disinfection task and stops the disinfection system when a human is detected around the robot in all directions. UVC light is dangerous for humans and thus the need for a human detection system that will protect them by disabling the disinfection process, as soon as a person is detected. This system uses a Raspberry Pi Camera with a Single Shot Detector (SSD) Mobilenet neural network to identify and detect persons. It also has a FLIR 3.5 Thermal camera that measures temperatures that are used to detect humans when within a certain range of temperatures. The normal human skin temperature is the reference value for the range definition. The results show that the fusion of both sensors data improves the system performance, compared to when the sensors are used individually. One of the tests performed proves that the system is able to distinguish a person in a picture from a real person by fusing the thermal camera and the visible light camera data. The detection results validate the proposed system.pt_PT
dc.description.sponsorshipThis work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMendonça, Hugo; Lima, José; Costa, Paulo; Moreira, António Paulo; Santos, Filipe (2021). Human detector smart sensor for autonomous disinfection mobile robot. In Pereira, Ana I.; Fernandes, Florbela P.; Coelho, João Paulo; Teixeira, João Paulo; Pacheco, Maria F.; Alves, Paulo; Lopes, Rui Pedro (Eds.) Optimization, learning algorithms and applications: first International Conference, OL2A 2021. Cham: Springer Nature. p. 171-186. ISBN 978-3-030-91884-2pt_PT
dc.identifier.doi10.1007/978-3-030-91885-9_13pt_PT
dc.identifier.isbn978-3-030-91884-2
dc.identifier.urihttp://hdl.handle.net/10198/25338
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer Naturept_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectSmart sensorpt_PT
dc.subjectHuman detectionpt_PT
dc.subjectNeural networkpt_PT
dc.titleHuman detector smart sensor for autonomous disinfection mobile robotpt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.citation.endPage186pt_PT
oaire.citation.startPage171pt_PT
oaire.citation.titleOptimization, learning algorithms and applications: first International Conference, OL2A 2021pt_PT
oaire.citation.volume1488pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameLima
person.givenNameJosé
person.identifierR-000-8GD
person.identifier.ciencia-id6016-C902-86A9
person.identifier.orcid0000-0001-7902-1207
person.identifier.ridL-3370-2014
person.identifier.scopus-author-id55851941311
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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relation.isAuthorOfPublication.latestForDiscoveryd88c2b2a-efc2-48ef-b1fd-1145475e0055
relation.isProjectOfPublication6e01ddc8-6a82-4131-bca6-84789fa234bd
relation.isProjectOfPublication.latestForDiscovery6e01ddc8-6a82-4131-bca6-84789fa234bd

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