This chapter addresses how visibility solutions based on Digital Product Memories (DPMs) developed in the SemProM project can be demonstrated in the logistics domain to guarantee carbon offset of transport and integrity control within supply chains. A demonstration system is presented to illustrate how a DPM can be used for computing, assessing, and reducing a product's carbon footprint. In addition, semi-active and active RFID and sensor solutions developed to monitor product integrity are described. Finally, the SemProM browser is presented as a system for end-users to access product information and get visibility over product integrity.
%0 Book Section
%1 KueckelhausMagerkurthBaus13p311
%A Kückelhaus, Markus
%A Magerkurth, Carsten
%A Baus, Jörg
%B SemProM: Foundations of Semantic Product Memories for the Internet of Things
%C Heidelberg
%D 2013
%E Wahlster, Wolfgang
%I Springer
%K v1205 springer paper embedded ai sensor product information rfid logistics zzz.spm
%P 311-327
%R 10.1007/978-3-642-37377-0_19
%T A SemProM Use Case: Tracking & Tracing for Green Logistics and Integrity Control
%X This chapter addresses how visibility solutions based on Digital Product Memories (DPMs) developed in the SemProM project can be demonstrated in the logistics domain to guarantee carbon offset of transport and integrity control within supply chains. A demonstration system is presented to illustrate how a DPM can be used for computing, assessing, and reducing a product's carbon footprint. In addition, semi-active and active RFID and sensor solutions developed to monitor product integrity are described. Finally, the SemProM browser is presented as a system for end-users to access product information and get visibility over product integrity.
@incollection{KueckelhausMagerkurthBaus13p311,
abstract = {This chapter addresses how visibility solutions based on Digital Product Memories (DPMs) developed in the {SemProM} project can be demonstrated in the logistics domain to guarantee carbon offset of transport and integrity control within supply chains. A demonstration system is presented to illustrate how a {DPM} can be used for computing, assessing, and reducing a product's carbon footprint. In addition, semi-active and active {RFID} and sensor solutions developed to monitor product integrity are described. Finally, the {SemProM} browser is presented as a system for end-users to access product information and get visibility over product integrity.},
added-at = {2013-04-03T18:12:02.000+0200},
address = {Heidelberg},
author = {K{\"u}ckelhaus, Markus and Magerkurth, Carsten and Baus, J{\"o}rg},
biburl = {https://www.bibsonomy.org/bibtex/2a898fdd33e9a5032d8b1476cdb818ddb/flint63},
booktitle = {SemProM: Foundations of Semantic Product Memories for the Internet of Things},
crossref = {Wahlster2013},
doi = {10.1007/978-3-642-37377-0_19},
editor = {Wahlster, Wolfgang},
groups = {public},
interhash = {cf74d2229667794de1fbb1f473c05ab8},
intrahash = {b3f27d49ed286a9324e2718c1794fd14},
keywords = {v1205 springer paper embedded ai sensor product information rfid logistics zzz.spm},
pages = {311-327},
publisher = {Springer},
timestamp = {2015-03-05T14:14:40.000+0100},
title = {A {SemProM} Use Case: Tracking \& Tracing for Green Logistics and Integrity Control},
username = {flint63},
year = 2013
}