Citation

Goh, Jin Lun and Ho, Sin Ban and Tan, Chuie Hong (2024) Weather-Based Arthritis Tracking: A Mobile Mechanism for Preventive Strategies. Journal of Informatics and Web Engineering, 3 (1). pp. 210-225. ISSN 2821-370X

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Abstract

Arthritis is a common joint disorder characterised by symptoms such as swelling, pain, stiffness, and limited joint movement. It primarily affects older individuals, women, and athletes. The advent of information technology has created opportunities for patients to manage their health conditions more effectively. Research indicates that weather can affect arthritis symptoms, with many patients experiencing severe discomfort during rainy weather due to the expansion of already inflamed tissues. However, there is currently no mobile application mechanism available that combines weather forecasting with health recommendations for arthritis patients, which means that patients may not have access to important information that could help them manage their symptoms. Furthermore, few research workflows have focused on weather conditions in online arthritis treatment systems. This research aims to develop a weather-based mobile system for arthritis tracking that provides health advice and alerts based on current and forecast weather conditions, as well as features to help patients track how weather affects their arthritis. This system utilises several tools for its development. The Flutter Framework is used for creating mobile apps, while Firebase is chosen as the cloud-hosted database. Visual Studio Code and Android Studio are utilised as the code editor and Android emulator, respectively. Information about weather forecasts is retrieved via the OpenWeather API. The application mechanism will feature a user-friendly interface to help users stay updated on weather forecasts, and it will collect data in a reliable and user-centric manner for generating robust evidence on health outcomes.

Item Type:	Article
Uncontrolled Keywords:	Arthritis Inflammation, Joint disorder, Weather Tracking Mechanism, Mobile Health Recommendation
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Mr. MUHAMMAD AZRUL MOSRI
Date Deposited:	02 Apr 2024 07:24
Last Modified:	02 Apr 2024 07:24
URII:	http://shdl.mmu.edu.my/id/eprint/12252

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