Aspect oriented context-aware and event-driven data processing for internet of things
Michal Trnka, Jan Svacina, Tomáš Černý, Eun-Jee Song · 2018
The Internet of Things is currently getting significant interest from the scientific community. Academia and industry are both focused on moving ahead in attempts to put Internet of Things in practical use. Sensors and other devices in the Internet of Things networks generate tremendous amounts of data. Most of the times those data carry some contextual information and thus could be used for context-aware application. However, handling the vast amount of data becomes increasingly demanding task. In this article we propose event-driven solution for context-aware applications. In our method events are generated by Internet of Things devices and further propagated to subscribed actions. It support event filtering based on the data the event carries with him, like temperature or location. We demonstrate feasibility of our solution and compare it with traditional approach.