Ontology of Perception Evaluation

Ontology of Perception: A Semantic Web Approach to Enhance Machine Perception

Today, many sensor networks and their applications employ a brute force approach to collecting and analyzing sensor data, and ignore the semantics inherent in the environmental data. Such an approach often wastes valuable resources – including both energy and computational resources – by unnecessarily tasking sensors and generating observations of minimal use. People, on the other hand, have evolved sophisticated mechanisms to efficiently perceive their environment. Such mechanisms include the use of background knowledge to determine what aspects of the environment to focus and a strong interdependent relationship between our ability to observe and perceive. In this paper, we develop an ontology of perception – derived from cognitive theory – that may be used to more efficiently convert observations into perceptions. We evaluate this approach by collecting and analyzing observations of weather conditions, and show up to 50% reduction in the number of observations necessary for analysis.