In this exploration work, big data gathered from smart devices have been utilized to recover the human activity patterns to enhance smart home occupant`s health status, as there is a great deal of financial investment in the advanced transformation as a push to give healthier biological communities to individuals. which generate massive volumes of fine-grained and indexical data that can be analyzed to support smart city services. In this paper, we propose a model that utilizes smart home big data as a means of learning and discovering human activity patterns for health care applications.In this transformation a more of smart-devices are prepared around and gives an arranged data that can be utilized to investigate the health data. In this examination, the work mostly centers on breaking down the big data separated from human activities for frequent pattern mining, cluster analysis, prediction to quantify and investigate the energy consumption changes likewise by inhabitants. This paper speaks to the need of breaking down energy-consumption pattern dependent on the machine level, which is totally identified with person behavior.

Smart Devices, Human Activity Patterns, Smart home, Cluster Analysis, Bayesian network

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