The elderly health monitoring platform based on spark

With the explosion of sensor data, it is hard for traditional health monitoring platforms to process big data concurrently or analyze data online. This paper proposes a novel elderly health monitoring platform which introduces memory-based computation framework Spark to carry out the analysis of the data clustering. On the basis of parallelization of SMV detection algorithm, the proposed platform implements online analysis of real-time data stream using Spark Streaming. Experimental results show that with a large of number of users accessing, fall detection and clustering analysis can be achieved efficiently.