Context based content aggregation for Social Life Networks

![CDATA[It is extremely useful to have right information at the right time. Social Life Networks (SLN) extend the capabilities of current social networks by combining them with the technological advances now found in Smartphones that include myriad of sensors and multimedia input and output capabilities to provide essential information to support livelihood activities. The challenge is to provide this information within the required context. For this we need to model the context by acquiring the physical data to provide meaningful abstractions with respect to the application domain and the needs of the users. We have developed a physical context model based on user profile, location, time and activity and a mapping to match the logical context of various data sources from which we can get the required information. Based on this model we have developed a SLN for farmers in Sri Lanka to provide agricultural information in the context of farming life cycle stages, location of their farm land, cultivation season and other economic parameters. In the field trails there was unanimous agreement among farmers that this application is very useful for them because they were able to get the required information in context.]]