Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
B. B. Zaidan
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
M. Hashim
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
M. A. Alsalem
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
A. H. Mohsin
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
K. I. Mohammed
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
A. H. Alamoodi
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
Odai Enaizan
Faculty of Business, Middle East University (MEU), Amman, Jordan
Shahad Nidhal
Department of Computer Technology Engineering, Dijlah University, Baghdad, Iraq
Omar Zughoul
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
Fayiz Momani
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
M. A. Chyad
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
Karrar Hameed Abdulkareem
Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia
Kareem Abbas Dawood
Department of Software Engineering and Information Systems, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
E. M. Almahdi
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
Ghailan A. Al Shafeey
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
M. J. Baqer
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia
This paper proposes a smart real-time health monitoring structured for hospitals' distributor based on wearable health data sensors. Health data were received from multiple heterogeneous wearable sensors, such as electrocardiogram (ECG), oxygen saturation sensor (SpO2), blood pressure monitor, and non-sensory measurement (text frame), from 500 patients with different symptoms. Triage level and healthcare services were identified based on the new four-level remote triage and package localization (4LRTPL). The numbers of healthcare services that represent hospital status were collected from 12 hospitals located in Baghdad city. This study constructed a decision matrix based on the crossover of “multi-healthcare services” and “hospital list” within Tier 4. The hospitals were then ranked using multi-criteria decision-making (MCDM) techniques, namely, integrated analytic hierarchy process (AHP) and vlsekriterijumskaoptimizacija i kompromisnoresenje (VIKOR). Mean ± standard deviation was computed to ensure that the hospital ranking undergoes systematic ranking for objective validation. This research provided scenarios and checklist benchmarking to evaluate the proposed and existing health recommender frameworks. Results corroborated that: 1) the integration of AHP and VIKOR effectively solved hospital selection problems; 2) in the objective validation, significant differences were recognized between the scores of groups, indicating that the ranking results were identical; 3) in evaluation, the proposed framework exhibited an advantage over the benchmark framework with a percentage of 56.25%; and 4) hospitals with multiple healthcare services received the highest ranks, whereas hospitals with fewer healthcare services received low ranks.