Proceedings of the 5th ACM international conference on Distributed event-based system
An approach for more efficient energy consumption based on real-time situational awareness
ESWC'11 Proceedings of the 8th extended semantic web conference on The semanic web: research and applications - Volume Part II
On complex event processing for real-time situational awareness
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
An ontology-based iot resource model for resources evolution and reverse evolution
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
I3WSN: Industrial Intelligent Wireless Sensor Networks for indoor environments
Computers in Industry
Integrated system for control and monitoring industrial wireless networks for labor risk prevention
Journal of Network and Computer Applications
Context-driven RDF data replication on mobile devices
Semantic Web - On real-time and ubiquitous social semantics
Hi-index | 0.00 |
Semantic Sensor Web enhances raw sensor data with spatial, temporal, and thematic annotations to enable high-level reasoning. In this paper, we explore how abductive reasoning framework can benefit formalization and interpretation of sensor data to garner situation awareness. Specifically, we show how abductive logic programming techniques, in conjunction with symbolic knowledge rules, can be used to detect inconsistent sensor data and to generate human accessible description of the state of the world from consistent subset of the sensor data. We also show how trust/belief information can be incorporated into the interpreter to enhance reliability. For concreteness, we formalize Weather domain and develop a meta-interpreter in Prolog to explain Weather data. This preliminary work illustrates synthesis of high-level, reliable information for situation awareness by querying low-level sensor data.