Embedding Semantic Product Memories in the Web of Things
C. Seitz, C. Legat, and J. Neidig. PerCom 2010 Workshops: Proceedings of the 8th Annual IEEE International Conference on Pervasive Computing and Communications Workshops, Mannheim, Germany, page 708-713. (2010)
DOI: 10.1109/PERCOMW.2010.5470525
Abstract
RFID is used to identify a wide range of work pieces or individual products for tracking their movements through the logistics chain. For future purposes the idea of storing only a single ID must be extended to a Product Memory. This memory stores data of the complete product life cycle. This paper introduces an architecture and an implementation for integrating data in product memories. Our contribution encompasses software modules for a uniform sensor access, a sensor data ontology and web interfaces for product memory applications.
PerCom 2010 Workshops: Proceedings of the 8th Annual IEEE International Conference on Pervasive Computing and Communications Workshops, Mannheim, Germany
%0 Conference Paper
%1 SeitzLegatNeidig10PERCOM
%A Seitz, Christian
%A Legat, Christoph
%A Neidig, Jörg
%B PerCom 2010 Workshops: Proceedings of the 8th Annual IEEE International Conference on Pervasive Computing and Communications Workshops, Mannheim, Germany
%D 2010
%K v1205 ieee paper embedded ai sensor network rfid product information web zzz.spm zzz.a.spm14
%P 708-713
%R 10.1109/PERCOMW.2010.5470525
%T Embedding Semantic Product Memories in the Web of Things
%X RFID is used to identify a wide range of work pieces or individual products for tracking their movements through the logistics chain. For future purposes the idea of storing only a single ID must be extended to a Product Memory. This memory stores data of the complete product life cycle. This paper introduces an architecture and an implementation for integrating data in product memories. Our contribution encompasses software modules for a uniform sensor access, a sensor data ontology and web interfaces for product memory applications.
%@ 978-1-4244-6605-4
@inproceedings{SeitzLegatNeidig10PERCOM,
abstract = {RFID is used to identify a wide range of work pieces or individual products for tracking their movements through the logistics chain. For future purposes the idea of storing only a single ID must be extended to a Product Memory. This memory stores data of the complete product life cycle. This paper introduces an architecture and an implementation for integrating data in product memories. Our contribution encompasses software modules for a uniform sensor access, a sensor data ontology and web interfaces for product memory applications.},
added-at = {2012-05-30T10:53:56.000+0200},
author = {Seitz, Christian and Legat, Christoph and Neidig, J\"{o}rg},
biburl = {https://www.bibsonomy.org/bibtex/27a17cfabbd8a1cd4532de58778b3dee2/flint63},
booktitle = {PerCom 2010 Workshops: Proceedings of the 8th Annual IEEE International Conference on Pervasive Computing and Communications Workshops, Mannheim, Germany},
doi = {10.1109/PERCOMW.2010.5470525},
file = {Preprint:2010/SeitzLegatNeidig10PERCOM.pdf:PDF},
groups = {public},
interhash = {6d42d2c10ef2558c2bd4b11ffcbf8009},
intrahash = {7a17cfabbd8a1cd4532de58778b3dee2},
isbn = {978-1-4244-6605-4},
keywords = {v1205 ieee paper embedded ai sensor network rfid product information web zzz.spm zzz.a.spm14},
pages = {708-713},
timestamp = {2018-04-16T12:05:00.000+0200},
title = {Embedding Semantic Product Memories in the Web of Things},
username = {flint63},
year = 2010
}