دانلود مقاله ISI انگلیسی شماره 148888
ترجمه فارسی عنوان مقاله

برداشت انرژی بر اساس اینترنت از چیزها و تجزیه و تحلیل داده های بزرگ برای نظارت بر سلامت هوشمند

عنوان انگلیسی
Energy-harvesting based on internet of things and big data analytics for smart health monitoring
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
148888 2017 17 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Sustainable Computing: Informatics and Systems, Available online 28 October 2017

پیش نمایش مقاله
پیش نمایش مقاله  برداشت انرژی بر اساس اینترنت از چیزها و تجزیه و تحلیل داده های بزرگ برای نظارت بر سلامت هوشمند

چکیده انگلیسی

Current advancements and growth in the arena of the Internet of Things (IoT) is providing great potential in the novel epoch of healthcare. The future of healthcare is expansively promising, as it advances the excellence of life and health of humans, involving several health regulations. Continual increases of multifaceted IoT devices in healthcare is beset by challenges, such as powering IoT terminal nodes used for health monitoring, data processing, smart decisions, and event management. In this paper, we propose a healthcare architecture which is based on an analysis of energy harvesting for health monitoring sensors and the realization of Big Data analytics in healthcare. The rationale of the proposed architecture is two-fold: (1) comprehensive conceptual framework for energy harvesting for health monitoring sensors; and (2) data processing and decision management for healthcare. The proposed architecture is a three-layered architecture that comprises: (1) energy harvesting and data generation; (2) data pre-processing; and (3) data processing and application. The proposed scheme highlights the effectiveness of energy-harvesting based IoT in healthcare. In addition, it also proposes a solution for smart health monitoring and planning. We also utilized consistent datasets on the Hadoop server to validate the proposed architecture based on threshold limit values (TLVs). The study demonstrates that the proposed architecture offers substantial and immediate value to the field of smart health.