Title :
Sensor ontologies: from shallow to deep models
Author :
Russomanno, David J. ; Kothari, Cartik ; Thomas, Omoju
Author_Institution :
Dept. of Electr. & Comput. Eng., Memphis Univ., TN, USA
Abstract :
This paper presents a practical approach to developing comprehensive sensor ontologies based upon deep knowledge models rather than capturing only superficial sensor attributes. It is proposed that the representation and utilization of deep sensor ontologies would enable a variety of sensor information system applications including sensor parts compatibility determination, dynamic sensor selection and tasking, and reasoning about systems of sensors in which data must be fused and queried from a variety of sensor types within a myriad of environments.
Keywords :
ontologies (artificial intelligence); sensor fusion; sensors; deep knowledge model; dynamic sensor selection; sensor information system; sensor ontologies; sensor parts compatibility determination; Intelligent sensors; Mathematical model; Ontologies; Semantic Web; Semiconductor process modeling; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Sensor systems and applications; Taxonomy;
Conference_Titel :
System Theory, 2005. SSST '05. Proceedings of the Thirty-Seventh Southeastern Symposium on
Print_ISBN :
0-7803-8808-9
DOI :
10.1109/SSST.2005.1460887