IoT-Edge-Cloud-Assisted Intelligent Framework for Controlling Dengue

被引:2
|
作者
Alqahtani, Abdullah [1 ]
Alsubai, Shtwai [1 ]
Bhatia, Munish [2 ]
机构
[1] Prince Sattam Bin Abdulaziz Univ, Coll Comp Engn & Sci, Alkharj 11942, Saudi Arabia
[2] Natl Inst Technol Kurukshetra, Dept Comp Applicat, Kurukshetra 136119, India
来源
IEEE INTERNET OF THINGS JOURNAL | 2024年 / 11卷 / 09期
关键词
Artificial neural network (ANN); Edge-cloud computing; Internet of Things (IoT); TRANSMISSION;
D O I
10.1109/JIOT.2023.3348101
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Over the last decade, Dengue infection has expanded more rapidly than any other viral illness. The current research investigates the vast potential of the Internet of Things (IoT), and Edge-cloud computing in reproving dengue virus (DGN) infection-related technological healthcare solutions. Specifically, a hierarchical healthcare framework is proposed for preventing the spread of DGN using Edge-cloud-assisted IoT technology. The presented system can monitor and forecast an individual's susceptibility to DGN infection in a ubiquitous manner. Using K-means clustering, the presented system determines an individual's DGN infection status and generates alert signals in real-time. In addition, the proposed technique employs cloud computing to monitor people healthcare impacted by DGN. Moreover, it ensures probabilistic predictions about susceptibility to the DGN virus using Bayesian belief networks and artificial neural networks. The proposed system can assess health vulnerability, thereby reducing the probability of health loss. The suggested system's validity and applicability are confirmed by experimental evaluation. The simulation results of the proposed system confirm its optimal performance in terms of temporal delay (14.15 s), classification efficacy [accuracy (91.66%), sensitivity (92.34%), specificity (90.25%), and F-measure (91.12%)], prediction effectiveness [error (0.23), and pearson coefficient (85%)], and stability (72%).
引用
收藏
页码:15682 / 15689
页数:8
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