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Mobile IoT Cloud-based Health Monitoring Dashboard Application for the Elderly

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dc.contributor.authorKadir A.D.I.A.en_US
dc.contributor.authorAlias M.R.N.M.en_US
dc.contributor.authorDzaki D.R.M.en_US
dc.contributor.authorAzizan A.en_US
dc.contributor.authorDin N.M.en_US
dc.contributor.authorid57426768900en_US
dc.contributor.authorid57426633700en_US
dc.contributor.authorid57427045600en_US
dc.contributor.authorid15130531400en_US
dc.contributor.authorid9335429400en_US
dc.date.accessioned2023-05-29T09:39:38Z
dc.date.available2023-05-29T09:39:38Z
dc.date.issued2022
dc.descriptionData visualization; Life cycle; mHealth; Monitoring; Average life; Cloud-based; Dashboard; Elderly health monitoring; Elderly people; Global health; Health monitoring; Health services; Life expectancies; Mobile IoT; Internet of thingsen_US
dc.description.abstractOver the years the population are increasing and currently, there are about 8 billion people residing globally. In time, the number of elderly people will increase due to a higher life expectancy over the years. In 1950, the average life cycle is at 46 years and in 2019 the projection expands to 72.6 years. The main reason for this increase is due to better global health services and quality of life. Mobile health technologies are being implemented in most areas related to the healthcare industry to aid elderly patients by monitoring and collecting data related to the diseases and their critical level. This paper described the design and development of an IoT health monitoring system for the elderly. This IoT system consists of two sensing modules, PI and P3. PI measures the body temperature, heart rate, and oxygen saturation (SpO2), while P3 is an accelerometer sensor that detects a fall. Data gathered from these sensors are dispatched wirelessly to the Raspberry Pi gateway and are later stored in a cloud database called InfluxDB. A mobile application is built using the Flutter framework for mobile data visualization purposes. Users can view four screens in the application, including the dashboard for data sensors PI and P3, the profile page, and the notification page. The dashboard displays the elderly data embedded using Grafana. If the patient falls, an alert (OneSignal) in the notification will be sent postfall instantaneously. � 2022 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ICSSA54161.2022.9870913
dc.identifier.epage166
dc.identifier.scopus2-s2.0-85138703166
dc.identifier.spage161
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85138703166&doi=10.1109%2fICSSA54161.2022.9870913&partnerID=40&md5=353f0f3b3e29c7d46246fb4a5b038ade
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/27107
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle4th International Conference on Smart Sensors and Application: Digitalization for Societal Well-Being, ICSSA 2022
dc.titleMobile IoT Cloud-based Health Monitoring Dashboard Application for the Elderlyen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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