Document Type
Article
Publication Date
5-2009
Abstract
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.
Repository Citation
Thirunarayan, K.,
Henson, C. A.,
& Sheth, A. P.
(2009). Situation Awareness via Abductive Reasoning for Semantic Sensor Data: A Preliminary Report. 2009 International Symposium on Collaborative Technologies and Systems: May 18-22, 2009, Baltimore, Maryland, USA, 111-118.
https://corescholar.libraries.wright.edu/knoesis/332
DOI
10.1109/CTS.2009.5067470
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Paper presented at the International Symposium on Collaborative Technologies and Systems, Baltimore, MD, May 18-22, 2009.