You are here

An Efficient Bit Vector Approach to Semantics-based Machine Perception in Resource-Constrained Devices

Title An Efficient Bit Vector Approach to Semantics-based Machine Perception in Resource-Constrained Devices
Author , ,
Venue 11th International Semantic Web Conference
Year 2012
Resource Type ConferencePaper
Keyword(s) Semantic Sensor Web,Sensor Data,Semantic Perception,Machine Perception,Mobile Device,Resource-Constrained Environments
Pages 149-164
Full Citation Cory Henson, Krishnaprasad Thirunarayan, and Amit Sheth, 'An Efficient Bit Vector Approach to Semantics-based Machine Perception in Resource-Constrained Devices,' In: Proceedings of 11th International Semantic Web Conference (ISWC 2012), Boston, Massachusetts, USA, November 11-15, 2012.
Abstract The primary challenge of machine perception is to define efficient computational methods to derive high-level knowledge from low-level sensor observation data. Emerging solutions are using ontologies for expressive representation of concepts in the domain of sensing and perception, which enable advanced integration and interpretation of heterogeneous sensor data. The computational complexity of OWL, however, seriously limits its applicability and use within resource-constrained environments, such as mobile devices. To overcome this issue, we employ OWL to formally define the inference tasks needed for machine perception - explanation and discrimination - and then provide efficient algorithms for these tasks, using bit-vector encodings and operations. The applicability of our approach to machine perception is evaluated on a smart-phone mobile device, demonstrating dramatic improvements in both efficiency and scale.
pdf
Additional Resources >>
Slideshare Link url

DISCLAIMER : Readers may view, browse, and/or download material for temporary copying purposes only, provided these uses are for noncommercial personal purposes. Except as provided by law, this material may not be further reproduced, distributed, transmitted, modified, adapted, performed, displayed, published, or sold in whole or in part, without prior written permission from the publisher.



Edit this page
<< Back to Knoesis Library  

© 2012 Kno.e.sis | 377 Joshi Research Center, 3640 Colonel Glenn Highway, Dayton, OH 45435 | (937 - 775 - 5217)