Context Handling

The Context Handling allows for identifying changes in the context of the environment. The current identified context is used to support the Deep Learning Engine. It uses monitored “raw data” provided by systems/virtual sensors, or the Runtime Monitoring and Verification component to derive the current context. The Context Handling is comprised by two main back-end services, the Context Monitoring service and the Context Extraction service. Furthermore, a repository for storing the internal data processed and created by Context Handling is implemented.

Context Monitoring: The Context Monitoring service uses available Context Monitors, that continuously monitor the data sources for new data provided. For the EP monitors are implemented that listen to the MoM. If new data is available, the monitored data is transformed into a data format that is usable by Context Extraction and stored in the repository of Context Handling. Afterwards the Context Extraction service is notified that new data is available.

Context Extraction: The Context Extraction Service continuously listens for monitored data provided by the Context Monitoring service. If new monitoring data is available, Context Extraction tries to identify the current context based on the monitored data, the context model and previously stored identified context. The current identified context is stored in the Context Repository. Furthermore, the current identified context is posted to the SmartCLIDE MoM. From there the Deep Learning Engine can retrieve the extracted context for further processing.

Using Context Handling

The Readme explains on how to configure, build and use the Context Handling