Sood Sandeep K, Mahajan Isha
Department of Computer Science and Engineering, GNDU, Regional Campus, Gurdaspur, Punjab, India.
Comput Ind. 2017 Oct;91:33-44. doi: 10.1016/j.compind.2017.05.006. Epub 2017 Jun 10.
Chikungunya is a vector borne disease that spreads quickly in geographically affected areas. Its outbreak results in acute illness that may lead to chronic phase. Chikungunya virus (CHV) diagnosis solutions are not easily accessible and affordable in developing countries. Also old approaches are very slow in identifying and controlling the spread of CHV outbreak. The sudden development and advancement of wearable internet of things (IoT) sensors, fog computing, mobile technology, cloud computing and better internet coverage have enhanced the quality of remote healthcare services. IoT assisted fog health monitoring system can be used to identify possibly infected users from CHV in an early phase of their illness so that the outbreak of CHV can be controlled. Fog computing provides many benefits such as low latency, minimum response time, high mobility, enhanced service quality, location awareness and notification service itself at the edge of the network. In this paper, IoT and fog based healthcare system is proposed to identify and control the outbreak of CHV. Fuzzy-C means (FCM) is used to diagnose the possibly infected users and immediately generate diagnostic and emergency alerts to users from fog layer. Furthermore on cloud server, social network analysis (SNA) is used to represent the state of CHV outbreak. Outbreak role index is calculated from SNA graph which represents the probability of any user to receive or spread the infection. It also generates warning alerts to government and healthcare agencies to control the outbreak of CHV in risk prone or infected regions. The experimental results highlight the advantages of using both fog computing and cloud computing services together for achieving network bandwidth efficiency, high quality of service and minimum response time in generation of real time notification as compared to a cloud only model.
基孔肯雅热是一种通过病媒传播的疾病，在受影响地区传播迅速。其爆发会导致急性疾病，可能会发展为慢性阶段。在发展中国家，基孔肯雅病毒（CHV）诊断解决方案不易获得且价格昂贵。此外，传统方法在识别和控制CHV疫情传播方面非常缓慢。可穿戴物联网（IoT）传感器、雾计算、移动技术、云计算以及更好的网络覆盖的突然发展和进步，提高了远程医疗服务的质量。物联网辅助的雾健康监测系统可用于在疾病早期识别可能感染CHV的用户，从而控制CHV的爆发。雾计算具有许多优点，如低延迟、最短响应时间、高移动性、增强的服务质量、位置感知以及在网络边缘的通知服务本身。本文提出了基于物联网和雾的医疗系统来识别和控制CHV的爆发。模糊C均值（FCM）用于诊断可能感染的用户，并立即从雾层向用户生成诊断和紧急警报。此外，在云服务器上，社交网络分析（SNA）用于表示CHV爆发的状态。从SNA图计算爆发角色指数，该指数表示任何用户接收或传播感染的概率。它还会向政府和医疗机构发出警告警报，以控制高风险或受感染地区的CHV爆发。实验结果突出了与仅使用云模型相比，同时使用雾计算和云计算服务在实现网络带宽效率、高服务质量以及生成实时通知的最短响应时间方面的优势。
