Mobile IoT cloud-based health monitoring dashboard application for the elderly

Over 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....

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Bibliographic Details
Main Authors: Abdul Kadir, Ahmad Dziaul Islam, Mohd. Alias, Mohamad Razin Naim, Mohd. Dzaki, Dzahir Rashidi, Azizan, Azizul, Md. Din, Norashidah
Format: Conference or Workshop Item
Published: 2022
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Online Access:http://eprints.utm.my/id/eprint/98937/
http://dx.doi.org/10.1109/ICSSA54161.2022.9870913
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Summary:Over 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.