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dc.rights.licenseopenen_US
hal.structure.identifierESTIA INSTITUTE OF TECHNOLOGY
dc.contributor.authorBOUSSAADA, Nesrine
hal.structure.identifierESTIA INSTITUTE OF TECHNOLOGY
dc.contributor.authorBOUSSAADA, Zina
hal.structure.identifierESTIA INSTITUTE OF TECHNOLOGY
dc.contributor.authorLLARIA, Alvaro
ORCID: 0000-0002-0348-6419
IDREF: 259161004
hal.structure.identifierESTIA INSTITUTE OF TECHNOLOGY
dc.contributor.authorTERRASSON, Guillaume
ORCID: 0000-0002-3468-5883
IDREF: 136426158
hal.structure.identifierESTIA INSTITUTE OF TECHNOLOGY
dc.contributor.authorCUREA, Octavian
ORCID: 0000-0002-5030-2088
IDREF: 68259131
dc.date.accessioned2023-04-04T13:19:31Z
dc.date.available2023-04-04T13:19:31Z
dc.date.issued2022-10
dc.date.conference2022-10-26
dc.identifier.isbn978-1-6654-5168-0, 978-1-6654-5169-7
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/172729
dc.description.abstractEnThe evolution towards the Industry 4.0 concept implies a huge development of the connectivity and the smart automation in all the industrial areas. For the chemical processes, the supervision systems are generally fairly basic, and a number of operations are still conducted by the operators. In order to simplify their daily tasks, expert systems able to discern each stage of the process and any possible drifts can be considered. To be implemented, the expert system needs a knowledge base which, in our case, will contain a set of images representative of the main stages of the process. The embedded system which will make the image capture must be autonomous from an energy point of view. Thus, the energy consumption optimization is necessary to ensure the maximal lifetime for the system. In this frame, this paper presents the energy management solution applied to an image acquisition system, based on a Raspberry Pi, for the chemical industry. The energy saving is achieved by the choice of the physical architecture, together with the application of a duty-cycle strategy.
dc.language.isoENen_US
dc.publisherIEEEen_US
dc.subject.enEnergy management
dc.subject.enRaspberry Pi
dc.subject.enDuty-cycle
dc.subject.enSmart industry
dc.title.enEnergy Consumption Optimization of a Raspberry Pi-based Image Acquisition Embedded System
dc.typeCommunication dans un congrès avec actesen_US
dc.identifier.doi10.1109/CISTEM55808.2022.10044049en_US
dc.subject.halSciences de l'ingénieur [physics]/Electroniqueen_US
bordeaux.page1-6en_US
bordeaux.hal.laboratoriesESTIA - Rechercheen_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionBordeaux INPen_US
bordeaux.institutionBordeaux Sciences Agroen_US
bordeaux.conference.title2022 IEEE International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM)en_US
bordeaux.countrytnen_US
bordeaux.title.proceeding2022 IEEE International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM)en_US
bordeaux.conference.cityTunisen_US
bordeaux.peerReviewedouien_US
bordeaux.import.sourcehal
hal.identifierhal-04000850
hal.version1
hal.exportfalse
workflow.import.sourcehal
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2022-10&rft.spage=1-6&rft.epage=1-6&rft.au=BOUSSAADA,%20Nesrine&BOUSSAADA,%20Zina&LLARIA,%20Alvaro&TERRASSON,%20Guillaume&CUREA,%20Octavian&rft.isbn=978-1-6654-5168-0,%20978-1-6654-5169-7&rft.genre=proceeding


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