| With the rapid development of technology such as mobile Internet, IoT, big data and etc., Smart health-care is welcoming significant progress, and leading the traditional medical industry into the era of information. The development of wearable medical devices and technology of big data has make progress in health services. The digital information system of traditional hospitals and other health care institutions is imperfect, which lead to lacking of a platform which can process a lot of health data in the medical wisdom technology effectively, especially lacking the ability of digging valuable information from huge data. Therefore, this thesis investigates how to design a complete user-friendly consumer service platform in order to solve the problem of massive wisdom medical data storage, process and extraction.In this thesis, by considering the characteristics of health data analysis and processing, a consumer-oriented health service platform is designed with the aid of Sugon TC4600 blade server and its distributed big data software Hadoop. The system structure is designed by combining Struts2 and Hadoop in a stratification manner. The platform can provide users with health services through analyzing and processing health data, in which FP-growth algorithm is utilized to accomplish parallel improvement based on MapReduce technology. MVC mode is designed based on Struts2, and data management, storage, mining and other interface are defined. Hadoop clustering is connected to the platform for big data analysis and processing. In order to prove the effectiveness of the platform, information related to decision-making is acquired by mining and analyzing the weather and disease data. The results analyzed and processed are displayed through Web page eventually.In conclusion, the developed user health service platform possesses the advantages of structure simplicity, function comprehensiveness and high efficiency, and basically meets the consumer demands. |
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