Combined Machine Learning and Semantic Modelling for Situation Awareness and Healthcare Decision Support

The average of global life expectancy at birth was 72 years in 2016 [1], however, the global healthy life expectancy at birth was only 63.3 years in the same year, 2016 [2]. Living a long life is not any more as challenging as assuring active and associated life [25]. We propose in this paper an IoT based holistic remote health monitoring system for chronically ill and elderly patients. It supports smart clinical decision help and prediction. The patient heterogeneous vital signs and contexts gathered from wore and surrounding sensors are semantically simplified and modeled via a validated ontology composed by FOAF (Friend of a Friend), SSN (Semantic Sensors Network)/SOSA (Sensor, Observation, Sample and Actuator) and ICNP (International Classification Nursing Practices) ontologies. The reasoner engine is based on a scalable set of inference rules cohesively integrated with a ML (Machine Learning) algorithm to ensure predictive analytic and preventive personalized health services. Experimental results prove the efficiency of the proposed system.