Identificador persistente para citar o vincular este elemento: https://accedacris.ulpgc.es/handle/10553/139741
Campo DC Valoridioma
dc.contributor.authorMontiel-Nelson, Juan A.en_US
dc.contributor.authorOttella, Marcoen_US
dc.contributor.authorAzzoni, Paoloen_US
dc.date.accessioned2025-06-09T11:21:11Z-
dc.date.available2025-06-09T11:21:11Z-
dc.date.issued2025en_US
dc.identifier.isbn9783982674100en_US
dc.identifier.issn1530-1591en_US
dc.identifier.otherScopus-
dc.identifier.urihttps://accedacris.ulpgc.es/handle/10553/139741-
dc.description.abstractH2TRAIN aligns with the ECS Strategic Research and Innovation Agenda 2023 (ECS-SRIA), addressing key challenges in integrating digital technologies for health-focused lifestyles through AI-enhanced networks. This project pioneers the use of graphene to develop autonomous biosensors within CMOS technology, supporting advancements in AI-powered health services and IoT applications. Beyond digital integration, H2TRAIN innovates in energy detection, collection, and storage, essential for embedding health and sports functions in IoT wearables through smart textile and system integration. The solutions will be rigorously tested and validated with insights from medical, sports, social sciences, and end-user feedback. Focused on remote assisted living, amateur sports training, and post-operative monitoring, H2TRAIN aims to drive innovation in the smart healthcare sector, where investment in semiconductor nanofabrication is limited by the small scale of medical applications.en_US
dc.languageengen_US
dc.sourceProceedings -Design, Automation and Test in Europe, DATE[ISSN 1530-1591], (Enero 2025)en_US
dc.subject33 Ciencias tecnológicasen_US
dc.subject.other1D And 2D-Materialsen_US
dc.subject.otherArtificial Intelligence (Ai)en_US
dc.subject.otherBiosensing Devicesen_US
dc.subject.otherEdge Computingen_US
dc.subject.otherEmbedded Intelligenceen_US
dc.subject.otherEnergy Harvestingen_US
dc.subject.otherHeterogeneous Integration Of Functionalityen_US
dc.subject.otherInternet Of Things (Iot)en_US
dc.subject.otherMore-Than-Moore Devicesen_US
dc.titleMulti-Partner Project: Enabling Digital Technologies for Holistic Health-Lifestyle Motivational and Assisted Supervision Supported by Artificial Intelligence Network (H2TRAIN)en_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference2025 Design, Automation and Test in Europe Conference, DATE 2025en_US
dc.identifier.doi10.23919/DATE64628.2025.10993023en_US
dc.identifier.scopus105006914694-
dc.contributor.orcid0000-0003-4323-8097-
dc.contributor.orcid0000-0001-7409-196X-
dc.contributor.orcid0000-0002-3324-6133-
dc.contributor.authorscopusid6603626866-
dc.contributor.authorscopusid6508255869-
dc.contributor.authorscopusid57225425630-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.date.coverdateEnero 2025en_US
dc.identifier.conferenceidevents155917-
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-TELen_US
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.event.eventsstartdate31-03-2025-
crisitem.event.eventsenddate02-04-2025-
crisitem.author.deptGIR IUMA: Instrumentación avanzada-
crisitem.author.deptIU de Microelectrónica Aplicada-
crisitem.author.deptDepartamento de Ingeniería Electrónica y Automática-
crisitem.author.orcid0000-0003-4323-8097-
crisitem.author.parentorgIU de Microelectrónica Aplicada-
crisitem.author.fullNameMontiel Nelson, Juan Antonio-
Colección:Actas de congresos
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