An IoT-aware approach for elderly-friendly cities

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dc.contributor.authorMulero, Rubén
dc.contributor.authorAlmeida, Aitor
dc.contributor.authorAzkune Galparsoro, Gorka
dc.contributor.authorAbril Jiménez, Patricia
dc.contributor.authorArredondo Waldmeyer, María Teresa
dc.contributor.authorPáramo Castrillo, Miguel
dc.contributor.authorPatrono, Luigi
dc.contributor.authorRametta, Piercosimo
dc.contributor.authorSergi, Ilaria
dc.date.accessioned2026-03-02T10:30:10Z
dc.date.available2026-03-02T10:30:10Z
dc.date.issued2018-03-12
dc.date.updated2026-03-02T10:30:10Z
dc.description.abstractThe ever-growing life expectancy of people requires the adoption of proper solutions for addressing the particular needs of elderly people in a sustainable way, both from service provision and economic point of view. Mild cognitive impairments and frailty are typical examples of elderly conditions which, if not timely addressed, can turn out into more complex diseases that are harder and costlier to treat. Information and communication technologies, and in particular Internet of Things technologies, can foster the creation of monitoring and intervention systems, both on an ambient-assisted living and smart city scope, for early detecting behavioral changes in elderly people. This allows to timely detect any potential risky situation and properly intervene, with benefits in terms of treatment's costs. In this context, as part of the H2020-funded City4Age project, this paper presents the data capturing and data management layers of the whole City4Age platform. In particular, this paper deals with an unobtrusive data gathering system implementation to collect data about daily activities of elderly people, and with the implementation of the related linked open data (LOD)-based data management system. The collected data are then used by other layers of the platform to perform risk detection algorithms and generate the proper customized interventions. Through the validation of some use-cases, it is demonstrated how this scalable approach, also characterized by unobtrusive and low-cost sensing technologies, can produce data with a high level of abstraction useful to define a risk profile of each elderly person.en
dc.description.sponsorshipCity4Age Project through the European Union’s Horizon 2020 Research and Innovation Programme under Grant 689731en
dc.identifier.citationMulero, R., Aitor, A., Gorka, A., Abril-Jiménez, P., Waldmeyer, M. T. A., Castrillo, M. P., Patrono, L., Rametta, P., & Sergi, I. (2018). An IoT-aware approach for elderly-friendly cities. IEEE Access, 6, 7941-7957. https://doi.org/10.1109/ACCESS.2018.2800161
dc.identifier.doi10.1109/ACCESS.2018.2800161
dc.identifier.eissn2169-3536
dc.identifier.urihttps://hdl.handle.net/20.500.14454/5289
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.rights© 2018 IEEE
dc.subject.otherElderly
dc.subject.otherIoT
dc.subject.otherLOD
dc.subject.otherMCI
dc.subject.otherMonitoring systems
dc.subject.otherRisk detection
dc.subject.otherSmart environments
dc.titleAn IoT-aware approach for elderly-friendly citiesen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.endPage7957
oaire.citation.startPage7941
oaire.citation.titleIEEE Access
oaire.citation.volume6
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
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