Same world, different words: Augmenting sensor output through semantics

This paper addresses the general problem of bridging the gap between sensor output and the structured reports needed and handled by end users in several practical applications. Sensors perform measurements used to characterize world entities according to their physical features, such as weight or speed or even more abstract features extracted from signal statistics such as spectral higher-order moments. The sensor outputs are usually provided to a human operator, allowing him to build, communicate and share with other humans a picture of a given situation. However in practice, humans often handle entities by considering their functions as it is the case in military intelligence reports rather than limiting their attention to physical or statistical properties. A possible solution to such a mismatch is to augment appropriately the vocabulary used to deliver the sensor outputs, allowing the operators to manipulate it efficiently in practical applications such as military intelligence analysis and dissemination. This paper presents a semantic approach developed for relating two complementary descriptions of data, one built upon experimental data collected using the SASNet system, the other being a military intelligence ontology called ONTO-CIF. The proposed method is based on ontology mapping and allows us to augment sensor data in order to cope with user needs.