Activity awareness in context-aware systems using software sensors

Context-aware systems being a component of ubiquitous or pervasive computing environment sense the users’ physical and virtual surrounding to adapt their behaviour accordingly. To achieve activity context tracking devices are common practice. Service Oriented Architecture is based on collections of services that communicate with each other. The communication between users and services involves data that can be used to sense the activity context of the user. SOAP is a simple protocol to let applications exchange their information over the web. Semantic Web provides standards to express the relationship between data to allow machines to process data more intelligently. This work proposes an approach for supporting context-aware activity sensing using software sensors. The main challenges in the work are specifying context information in a machine processable form, developing a mechanism that can understand the data extracted from exchanges of services, utilising the data extracted from these services, and the architecture that supports sensing with software sensors. To address these issues, we have provided a bridge to combine the traditional web services with the semantic web technologies, a knowledge structure that supports the activity context information in the context-aware environments and mapping methods that extract the data out of exchanges occurring between user and services and map it into a context model. The Direct Match, the Synonym Match and the Hierarchical Match methods are developed to put the extracted data from services to the knowledge structure. This research will open doors to further develop automated and dynamic context-aware systems that can exploit the software sensors to sense the activity of the user in the context-aware environments

Mapping for activity recognition in the context-aware systems using software sensors

Context-aware systems are concerned with identifying the context of a user and then to either provide that information based on queries or to automatically decide on appropriate actions to be taken. Some context aspects (such as location) are easy to sense through hardware, while the activity of a user has shown to be somewhat elusive to being sensed with hardware sensors. As users use web services more frequently they are exchanging messages with the services through the SOAP protocol. SOAP messages contain data, which is valuable if gathered and interpreted right - especially as this data can be shedding information on the activity of a user that goes beyond "sitting at the computer and typing". We have developed software sensors, essentially based on monitoring SOAP messages and inserting data for further reasoning and querying into a semantic context model. In this paper we consider a solution to map the data from a SOAP message to our OWL ontology model automatically. Specifically, we explain the methodology to map from SOAP messages to an existing structure of knowledge