A Fog-Based Healthcare Framework for Chikungunya
Sandeep K. Sood, Isha Mahajan · IEEE Internet of Things Journal · 2017
Chikungunya virus is an infection which is transmitted to humans by the bite of Aedes agypti and Aedes albopictis mosquitoes. It causes deterioration in health leading to multiorgan failure. Diagnostic tests for this virus are not easily available and affordable in developing countries. The medical technologies are not so efficient in diagnosing and preventing the outbreak of Chikungunya virus. Healthcare services based on a fog-cloud technology are emerging as a proactive and effective solution to provide remote detection and monitoring of users. A fog assisted healthcare system can be used to diagnose users infected by Chikungunya virus in an initial state of their infection so that proper treatment can be given to them on time to enable fast recovery. In this paper, a fog assisted cloud-based healthcare system is designed to diagnose and prevent the outbreak of this virus. Initially, a decision tree is used to classify the category of user's infection depending on his/her health symptoms and diagnostic alerts are immediately generated on the user's mobile phone from fog layer. Furthermore, the state of Chikungunya virus outbreak is represented using temporal network analysis (TNA) on cloud layer using proximity data. Various outbreak metrics from TNA graph are calculated which indicate the probability to receive or transmit Chikungunya infection to human beings. Results depict that J48 decision tree classifier has higher accuracy and lower response time in determining the level of Chikungunya virus infection as compared to other classification algorithms. Moreover, alert generation based on real-time healthcare data further enhances the utility of the proposed system.