Paving the Way for a Real-Time Context-Aware Predictive Architecture

Abstract

Internet of Things society generates and needs to consume huge amounts of data in a demanding context-aware scenario. Such exponentially growing data sources require the use of novel processing methodologies, technologies and tools to facilitate data processing in order to detect and prevent situations of interest for the users in their particular context. To solve this issue, we propose an architecture which making use of emerging technologies and cloud platforms can process huge amounts of heterogeneous data and promptly alert users of relevant situations for a particular domain according to their context. Last, but not least, we will provide a graphical tool for domain experts to easily model, automatically generate code and deploy the situations to be detected and the actions to be taken in consequence. The proposal will be evaluated through a real case study related to air quality monitoring and lung diseases in collaboration with a doctor specialist on lung diseases of a public hospital.