Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

A Literature Review of Sensor Ontologies for Manufacturing Applications

Published

Author(s)

Craig I. Schlenoff, Tsai Hong Hong, Roger D. Eastman

Abstract

The purpose of this paper is to review existing sensor and sensor network ontologies to understand whether they can be reused as a basis for a manufacturing perception sensor ontology, or if the existing ontologies hold lessons for the development of a new ontology. We develop an initial set of requirements that should apply to a manufacturing perception sensor ontology. These initial requirements are used in reviewing selected existing sensor ontologies. This paper describes the steps for 1) extending and refining the requirements; 2) proposing hierarchical structures for verifying the purposes of the ontology; and 3) choosing appropriate tools and languages to support such an ontology. Some languages could include OWL (Web Ontology Language) [1]and SensorML (Sensor Markup Language) [2]. This work will be proposed as a standard within the IEEE Robotics and Automation Society (RAS) Ontologies for Robotics Automation (ORA) Working Group [3].
Proceedings Title
2013 IEEE International Symposium on Robotics and Sensors Environment (ROSE)
Conference Dates
October 21-23, 2013
Conference Location
Washington, DC

Keywords

sensor ontology, manufacturing perception, requirements, literature review

Citation

Schlenoff, C. , , T. and Eastman, R. (2013), A Literature Review of Sensor Ontologies for Manufacturing Applications, 2013 IEEE International Symposium on Robotics and Sensors Environment (ROSE), Washington, DC, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=914024 (Accessed March 19, 2024)
Created October 23, 2013, Updated February 19, 2017