Energy efficient IoT-Fog based architectural paradigm for prevention of Dengue fever infection

Abstract

Dengue is one of the most common and widespread infectious illnesses in humans transmitted by female Aedes albopictis. The prevalence of Dengue cases has increased substantially leading to human morbidity. Inadequate availability of healthcare professionals and inaccessibility to healthcare institutions have aggravated the problem. The traditional medical technologies are too antiquated to serve the purpose. The innovative latest technologies like Internet of Things (IoT), Cloud Computing, Fog Computing have made real-time and remote healthcare possible with huge success. In this paper, an IoT based Fog–Cloud enabled system for monitoring, assessment and control of Dengue Fever has been proposed. IoT sensors acquire data about a large spectrum of health as well as environmental factors that contribute to infection. The battery constrained sensors set their sampling rate according to the degree of cruciality that saves power to make battery long lasting. The Fog layer employs Support Vector Machine (SVM) for Dengue infection evaluation with least latency and sends alerts including precautionary measures to the users, hospital officials and government agencies. Moreover, the proposed system utilizes Temporal Network Analysis (TNA) and Google map service to categorize areas as infected, uninfected or risk prone. The experimental results are evaluated by a number of analytical parameters to investigate the effect of proposed system. SVM performs the best in terms of accuracy, recall, specificity, precision and f-measure with values 93%, 95%, 89%, 94% and 95% respectively. Furthermore, TNA based outbreak assessment gives valuable inputs for the government institutions to control the outbreak.