QoS-Aware Smart Phone-Based User Tracking Application to Prevent Outbreak of COVID-19 in Saudi Arabia.
Arwa MashatAliaa M AlabdaliPublished in: Computational intelligence and neuroscience (2022)
Diverse variants of COVID-19 are repeatedly making everyday living unstable. In reality, the conclusive retort of this highly contagious virus still is in incognito mode. The health experts' primary guideline on the possible prevention of this disease outbreak, including a list of restrictions and confinements, is insufficient in case of any public congregation. As a result, the demand for precise and upgraded real-time COVID-19 tracking and prevention-based applications increases. However, most of the existing android-based applications face a lack of data security and reliability that cannot satisfy the additional quality of service (QoS) requirements. This paper proposes an easy-to-operate android-based multifunctional application to track individuals' health situations, allow uploading scanning report by the authorized organization like universities, mosques, school, and hospitals and helps the users to maintain guidelines via manageable steps. This article offers a three-layered QoS aware service-oriented task scheduling model upon multitasking android-based frontend focusing the cognitive-based AI applications in healthcare with a continual learning paradigm. Designed model is competent to optimize heterogeneous service scheduling and can minimize data delivery time, as well as the resource cost.
Keyphrases
- healthcare
- mental health
- coronavirus disease
- sars cov
- electronic health record
- big data
- physical activity
- drug delivery
- health information
- public health
- artificial intelligence
- respiratory syndrome coronavirus
- copy number
- machine learning
- deep learning
- dna methylation
- quality improvement
- gene expression
- social media
- data analysis
- climate change
- mass spectrometry
- global health
- virtual reality
- cancer therapy
- metal organic framework