%0 Book Section %1 ChoPreissinger13p107 %A Cho, Young-Jae %A Preißinger, 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 automotive middleware architecture zzz.spm %P 107-123 %R 10.1007/978-3-642-37377-0_7 %T Capturing Sensor Data in the SemProM Automotive Scenario %X This chapter presents the concept and implementation of a smart SemProM to capture and process sensor data in the context of the automotive DPM architecture called the DPM Sensor Platform. Two exemplary use cases of the development process were chosen to illustrate the evolutionary and also revolutionary use of the DPM Sensor Platform. The first one shows how existing systems can evolve by replacing parts of them with this platform, and the resulting benefits. The second one highlights the advantages of the integration of this platform in the holistic automotive DPM architecture and serves as an example for our proposal for a new paradigm for handling sensor data in the automotive context. Based on these use cases the requirements are derived, system, hardware, and software concepts are presented, and the prototypes are described.

@incollection{ChoPreissinger13p107, abstract = {This chapter presents the concept and implementation of a smart {SemProM} to capture and process sensor data in the context of the automotive {DPM} architecture called the {DPM} Sensor Platform. Two exemplary use cases of the development process were chosen to illustrate the evolutionary and also revolutionary use of the {DPM} Sensor Platform. The first one shows how existing systems can evolve by replacing parts of them with this platform, and the resulting benefits. The second one highlights the advantages of the integration of this platform in the holistic automotive {DPM} architecture and serves as an example for our proposal for a new paradigm for handling sensor data in the automotive context. Based on these use cases the requirements are derived, system, hardware, and software concepts are presented, and the prototypes are described.}, added-at = {2013-04-03T18:11:57.000+0200}, address = {Heidelberg}, author = {Cho, Young-Jae and Prei{\ss}inger, J{\"o}rg}, biburl = {https://www.bibsonomy.org/bibtex/2469c9ae2cda2b7f6e991a17165d085e6/flint63}, booktitle = {SemProM: Foundations of Semantic Product Memories for the Internet of Things}, crossref = {Wahlster2013}, doi = {10.1007/978-3-642-37377-0_7}, editor = {Wahlster, Wolfgang}, groups = {public}, interhash = {6f24a83e698b6fac171f26386caf03b4}, intrahash = {571c2ae2d27df5f2f4f32b1bd04d8ed3}, keywords = {v1205 springer paper embedded ai sensor product information rfid automotive middleware architecture zzz.spm}, pages = {107-123}, publisher = {Springer}, timestamp = {2015-03-05T14:05:19.000+0100}, title = {Capturing Sensor Data in the {SemProM} Automotive Scenario}, username = {flint63}, year = 2013 }