The Design And Implementation Of Intelligent Health System Based On Cloud Storage

At present, China has entered the aging society, and the degree of aging society will be growing as time going on. Besides, the health care system of our society is imperfection, health care structure is unreasonable, the distribution of medical resources is disproportionate. These aspects lead to Chinese traditional old-age care model needed to be improved. With the appearance of the Internet technology, big data and cloud computing technology, "Internet+Health Management+Intelligent Old-age Care System," a new model of old-age care comes into being. Therefore, a design based on the intelligent of health’s big data management system, fulfilling the information sharing and intelligence analysis, which helps solving the problem of old-age care.Cloud storage is the development and extension of cluster applications, grid computing and distributed technology and other technologies. Cloud storage is easy to expand, as you can expand the storage according to the number of server users and space, without affecting the front-end user’s service from the server. Meanwhile, cloud storage can realize the sharing of resources within the network, with the data being stored concentrative, which helps improve the resource utilization ratio. The server stores data with a backup, which help effectively preventing data loss and ensuring data reliability.In this paper, we design big data management system based on intelligent and health with the theory of cloud storage. After a clear system design aim, with specific example used in the analysis of the system requirements, we design the system architecture, divide the system module, and then give the detailed design of each module. The system uses HBase database and MySQL database combination to store the data, and uses MapReduce computing model processing data in parallel. The system achieves to store large-scale collected data, using a secondary index query against HBase’s non-Rowkey field data, which help to improve the efficiency of data query. The system provides data migration from inner and outer to HBase database correspondingly.In this paper, we deploy the cluster operating environment in the experiment part, and confirm the feasibility of system storage and querying huge amounts of data by various testing, and confirm the system internal migration from MySQL database data to HBase database being completely and efficiently.