Mining Human Activity Patterns from Smarthome Big Data by using MapReduce Algorithm
Dr. V. Karpagam, Sri Ramakrishna Engineering College, Coimbatore; M. U. Pooja ,Sri Ramakrishna Engineering College, Coimbatore; M. Swathi ,Sri Ramakrishna Engineering College, Coimbatore
Hadoop on Big Data, MapReduce, Frequent Pattern
Healthcare service is one of the most challenging aspects that is greatly affected by the migration of people to city centres. Cities are currently embracing massive digital transformation in an effort to support and provide a healthier environment. In such transformation millions of homes are being equipped with smart devices eg.smart meters, sensors etc which generate large volumes of data that can be analyzed to support health care services. The challenge is how to mine complex interdependencies among different appliances usage within a home where multiple data streams are occurring. The main goal is to discover human behavioural characteristics as an approach to understand and predict their activities that could indicate health issues. The human activity datasets which are generated by the smart meters are mined using the Big Data algorithms. If there is no usage of any appliances the result is given as an input to the health care application for further alerting needs.
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Paper ID: GRDCF007002
Published in: Conference : National Conference on Emerging Trends in Electrical, Electronics and Computer Engineering (ETEEC - 2018)
Page(s): 7 - 11
Published in: Conference : National Conference on Emerging Trends in Electrical, Electronics and Computer Engineering (ETEEC - 2018)
Page(s): 7 - 11