Fog–Cloud Assisted IoT-Based Hierarchical Approach For Controlling Dengue Infection. (8th April 2020)

• Record Type: Journal Article
• Authors: Sood, Sandeep Kumar; Sood, Vaishali; Mahajan, Isha; Sahil,
• Is Part Of: Computer journal. Volume 65:Number 1(2022)
• Page Start: 67
• Page End: 79
• Publication Date: 2020-04-08
• Subjects: arboviral diseases -- Internet of things (IoT) -- fog computing -- vector-borne disease -- cloud computing -- artificial neural network (ANN) -- k-means clustering (KMC) -- Bayesian belief network (BBN) -- global positioning system (GPS); Computers -- Periodicals; 005.1
• DOI: 10.1093/comjnl/bxaa005
• Languages: English
• ISSNs: 0010-4620

Abstract

Abstract: The past five decades have witnessed the unprecedented contribution of arboviral diseases towards global morbidity and disability. It is primarily attributed due to unplanned urbanization, population explosion and globalization. Out of these, dengue is considered the most important arboviral disease because of its predominant growth in the past. The presented study explores the immense potential of Internet of things (IoT), fog and cloud computing for providing technology-based healthcare solutions for dengue virus (DENV) infection. In this paper, a hierarchical healthcare computing system for controlling DENV infection using fog–cloud-assisted IoT is proposed. This system provides a real-time remote diagnosis of DENV infection in individuals and monitors and predicts their health sensitivity during its infection period. The system uses fog computing to diagnose the DENV infection status of the individuals using $k$ -means clustering and generates immediate diagnostic alerts to individuals, at the fog layer. Furthermore, the system uses cloud computing to monitor and predict the probabilistic health sensitivity of the DENV-infected individuals using Bayesian belief network and artificial neural network, respectively, at the cloud layer. The prediction of health sensitivity in the proposed system helps the infected individuals and healthcare agencies in determining the health vulnerability of DENV-infected individuals and preventing severe or permanent health losses in the future. The proposed system is experimentally evaluated using well-defined approaches, which conform to its validity and applicability. The results obtained from the experimental evaluations of the proposed system acknowledge the performance superiority and high efficiency of the system in delivering DENV-related healthcare services in real time.