Blackboard-based Sensor Interpretation using a Symbolic Model of the Sources of Uncertainty in Abductive Inferences (original) (raw)

Situation Awareness via Abductive Reasoning for Semantic Sensor Data: A Preliminary Report

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.

Evaluating Uncertainty Representation and Reasoning

2011

Abstract—High-level fusion of hard and soft information from diverse sensor types still depends heavily on human cognition. This results in a scalability conundrum that current technologies are incapable of solving. Although there is widespread acknowl-edgement that an HLF framework must support automated knowledge representation and reasoning with uncertainty, there is no consensus on the most appropriate technology to satisfy this requirement. Further, the debate among proponents of the various approaches is laden with miscommunication and ill-supported assumptions, which inhibits advancement of HLF research as a whole. A clearly defined, scientifically rigorous evaluation framework is needed to help information fusion researchers assess the suitability of various approaches and tools to their applications. This paper describes requirements for such a framework and describes a use case in HLF evaluation.