Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/21200
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dc.contributor.authorLousado, José Pauloen_US
dc.contributor.authorPires, Ivan Miguelen_US
dc.contributor.authorZdravevski, Eftimen_US
dc.contributor.authorAntunes, Sandraen_US
dc.date.accessioned2022-07-19T08:49:07Z-
dc.date.available2022-07-19T08:49:07Z-
dc.date.issued2021-07-19-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/21200-
dc.description.abstractThe rapid development and widespread use of information and telecommunication technologies do not mitigate, in many situations, information exclusion, nor the physical isolation of people—mainly that of the elderly living in remote locations, whose mobile network coverage is deficient or non-existent, preventing them from accessing health care, be it routine follow-up procedures or emergencies. Addressing this, we raise the question that guides our study: how can we monitor the elderly’s residence and health conditions, detect falls, and track their movement in the vicinity of their homes in a non-intrusive manner? To answer this question, we present a system prototype that uses affordable, low-cost, and low-energy equipment with media and data processing, supported by LoRa (Long Range) and ESP32 microcontrollers, coupling several sensors. As a result, it is possible to monitor sensors that predict and detect falls or other risk events for the user, e.g., fire, with authorized persons and entities, family members, civil protection, and security forces accessing the gathered data, assuring their security. We conclude that the system could decisively improve people’s quality of life, particularly those of the elderly who live in remote places with greater vulnerability.en_US
dc.publisherMDPIen_US
dc.relation.ispartofElectronicsen_US
dc.subjectIoT; LoRaWAN; pervasive systems; sensor data analytics; The Things Network; remote monitoringen_US
dc.titleMonitoring the Health and Residence Conditions of Elderly People, Using LoRa and the Things Networken_US
dc.typeJournal Articleen_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
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