A Mobile Home Monitoring System Based On Cloud Computing

Mobile medical promoted by the development of information is the combination of modern technology and medical industry.Compared to traditional medical procedure,more efficient and effective medical service and medical information can be provided by Mobile medical.As a carrier of various information in the interaction between doctors and patients,mobile terminal equipment has played an important role.However,the calculation and storage issues in the equipment have brought restrictions to the development of mobile medical.A mobile home monitoring system based on cloud computing is presented in this paper.The cloud environment provides storage space and computing environment for the system,thus reducing the requirement of mobile terminals.The main contents of this paper are as follows:Firstly,After the content of Mobile Medical is elaborated,tthe current development and technology trend are researched.According to the needs of existing mobile medical,the overall framework of domestic mobile medical based on cloud computing is established in this paper.Detailed layers in the framework are designed.The important module settings and logical structures of the system are studied in detail.Secondly,key technologies of mobile medical and cloud computing are studied,including Android application development technology,Hadoop and MapReduce in cloud computing technology and data mining technology.Then domestic mobile medical based on cloud computing is achieved by the combination of the theories and back-front labor method.The system is divided into Android application and data mining platform based on distributed C4.5 decision tree algorithm.According to the idea of distributed storage,the system database is divided into local SQLite database and cloud database MySQL and distributed file system HDFS,which manage the system data together.The hardware system of the data acquisition module is designed,and the design method and implementation process of the Android application are described in detail.Besides,the clustering algorithm and classification algorithm are used to mine the medical data,and the classification model and clustering result of medical data are obtained.The distributed C4.5 decision tree algorithm based on Hadoop platform is designed and implemented,and the design idea and implementation process of the algorithm are emphatically elaborated.On the basis of the algorithm,the human body data mining platform based on Weka platform is designed,to realize the module of patient management,data preprocessing and data mining.From the experimental results,it is found that the algorithm of distributed C4.5 decision tree algorithm is much more efiicient than ordinary decision tree algorithm in dealing with large-scale data set,and it is positively correlated with the number of Hadoop cluster nodes.