Performance analysis of various Map Reduce (MR) Models Using Internet of Things (IoT) Based Prediction of Cardiovascular Disease

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N.Rajesh Pandian, D.Shanthi


In the modern era, Internet of Things (IoT) occupied the advanced features in the information and communication fields. The IoT platform is very useful for the human’s healthcare monitoring in the various areas such as patient information management, real-time monitoring and healthcare management. According to the report, the mortality rate of (Cardiovascular Disease) CVD is more than 17.9 million globally for a year. Therefore the IoT data for CVD are very massive and huge in the size which is hard to access and extract information from it. The advanced Technique of Map Reduce (MR) model is used for a large set of data for the health predictions especially for the CVD. In this work, the survey of IoT based MR model is presented to observe the performance based accuracy and time consumptions. The basic of MR model is also discussed and then the overall performance of CVD Prediction is tabulated. The finest performance is determined from a survey in terms of accuracy, time consumption and error rate.

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