Multiple MapReduce functions for health care monitoring in a smart environment

MapReduce function is a programming paradigm for processing input datasets in a parallel manner. In this paper, we have utilized this function for identifying and predicting health data collected from smart homes to help elderly people to live independently in their own home longer away from hospitals. Statistical techniques running in parallel multiple MapReduce functions are used. The proposed approach is implemented in a smart home environment equipped with a wireless network of sensor data. Two case studies, which are extracted from real environments, are used to validate the results. The experiment results show that our approach successfully identifies the influence outliers and efficiently computing large health data.