Internet of things based context aware health care services

The enhancement in the number of sensors deployed to collect every single bit of information to develop intelligent applications is potentially growing in today's Internet of Things paradigm. The acquired data from sensors is to be inferred into meaningful information for decision making to address real world situations. Context information modeling and reasoning is one of the investigative research concern in the design and development of smart health care applications. As the accessed information is inherently imperfect, we propose a computational intelligence technique to analyze uncertainty associated with sensor data. In this paper, we propose Context Information, Observation and Belief (C-IOB) model from the perspective of in-hospital environment and the analysis is based on Bayesian network to deal with imprecise information. The proposed model provides a relevant service based on our research findings. © 2019 IEEE.