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Hidden Markov model and Internet of Things hybrid driven smart hospital

Based on the advancements in pervasive healthcare our perception of healthcare is changing quite fast. For any standard existing Hospital Information System (HIS) there are several major problems that hinders automation like, fixed information point or inflexible networking mode. In our paper, Internet of Things (IOT) based platform has been used for a better automation and faster decision making related executions in the smart hospital. Hidden Markov Models (HMM) offers scope for better predictive analysis for its dynamic probabilistic nature and helped us developing a dense sensing approach based on traces of activities in a hospital. A need-based HMM-IOT hybrid has been used for the smart hospital scheme proposed here, and it continuously synchronizes itself with the current spectral analysis data of the bio-signals of the admitted patients acquired by non-invasive processes like Electroencephalogram, Electromyogram, Electrocardiogram etc. The results of the experimentation are really promising.