Big healthcare data for Trivial client having Novel Smart Attire (NSA)

Big Data and Big Data technologies are changing the world. Healthcare is no exemption. Hospitals need to face and solve Big Data problems including collecting, processing, storing, analysing and retrieving the real-time and accumulated historical healthcare data. Big Data technologies will benefit medicine by precise diagnosis, correct treatment decisions and individualized medicine prescriptions, effective prevention planning for avoiding preventable deaths, feasible clinical trial testing outcomes or conclusions drawn on a specific medical drug for a disease, faster discovery of the root-causes and cures of many diseases such as the variety of cancers and age-related diseases; and timely prediction of disease epidemics. Big Data in healthcare emerges from the large electronic health datasets. These datasets are very difficult to manage with conventional hardware and software. In this research proposal, the emotions of the patients are monitored continuously by using Smart Attire, which collects the data and transmits for further processing and actions. The ordering system, named as Trivial client, is proposed and expanded to improve the execution of the records, that are built to hits ratio, by empowering the bigger list quality space that in class ordering arrangements. This facilitates efficient and high-throughput image processing with parallel programs typically executed on a cluster. It provides a solution for how to store a large collection of images on the Hadoop Distributed File System and make them available for efficient distributed processing.