304
M. Noura et al.
machine learning algorithm, (3) a dataset of smart car ontologies that we collected,
is analyzed by the k-means algorithm, and (4) the extraction of the most common
terms from the ontology dataset for the automotive sector. Our KEAS findings can be
used as a starting point for further domain-specific investigations (e.g., Volvo willing to integrate semantic web) and for future information extraction from structured
knowledge.
Keywords Internet of Things (IoT) · Knowledge directory service · Semantic
ontology interoperability · Ontology validation · Reusability · Semantic Web of
Things (SWoT) · Semantic web technologies · Reusable knowledge
1 Highlights
• Reusing knowledge already designed for knowledge-based smart car projects.
• Automatic knowledge extraction for the automotive sector based using the k-mean
machine learning algorithm.
2 Introduction
How to understand better the results provided by Google to build the future “smart
vehicle-centric” applications? What is the knowledge expertise required to build
a smart vehicle application such as the driver assistance system? According to PC
magazine,
1 a smart car is an automobile with advanced electronics. Microprocessors
have been used in car engines since the late 1960s and have steadily increased in
usage throughout the engine and drivetrain to improve stability, braking and general
comfort. According to Gartner’s 2018 prediction,
2 “IoT platforms”, “Autonomous
Driving Level 4”, and “Knowledge Graphs” are the next challenges for the coming
5–10 years or even beyond.
Automotive companies (e.g., Toyota
3 [1], BMW [2–5], Renault [6]) are already
employing Internet of Things (IoT) and Semantic Web technologies. BMW Autonomous Driving in the Internet of Cars Summer School
4 demonstrates interest in IoT
technologies and even Semantic Web technologies [3]. BMW is designing the Vehicle
Signal and Attribute (VSSO) ontology
5 [2] and the Vehicle Driving Context (VDC)
1 http://bit.ly/2xMZQDv.
2 https://gtnr.it/2SgUvOi.
3 http://bit.ly/2Y3A1xL.
4 http://www.bmwsummerschool.com/.
5 http://automotive.eurecom.fr/vsso.
M. Noura et al.
machine learning algorithm, (3) a dataset of smart car ontologies that we collected,
is analyzed by the k-means algorithm, and (4) the extraction of the most common
terms from the ontology dataset for the automotive sector. Our KEAS findings can be
used as a starting point for further domain-specific investigations (e.g., Volvo willing to integrate semantic web) and for future information extraction from structured
knowledge.
Keywords Internet of Things (IoT) · Knowledge directory service · Semantic
ontology interoperability · Ontology validation · Reusability · Semantic Web of
Things (SWoT) · Semantic web technologies · Reusable knowledge
1 Highlights
• Reusing knowledge already designed for knowledge-based smart car projects.
• Automatic knowledge extraction for the automotive sector based using the k-mean
machine learning algorithm.
2 Introduction
How to understand better the results provided by Google to build the future “smart
vehicle-centric” applications? What is the knowledge expertise required to build
a smart vehicle application such as the driver assistance system? According to PC
magazine,
1 a smart car is an automobile with advanced electronics. Microprocessors
have been used in car engines since the late 1960s and have steadily increased in
usage throughout the engine and drivetrain to improve stability, braking and general
comfort. According to Gartner’s 2018 prediction,
2 “IoT platforms”, “Autonomous
Driving Level 4”, and “Knowledge Graphs” are the next challenges for the coming
5–10 years or even beyond.
Automotive companies (e.g., Toyota
3 [1], BMW [2–5], Renault [6]) are already
employing Internet of Things (IoT) and Semantic Web technologies. BMW Autonomous Driving in the Internet of Cars Summer School
4 demonstrates interest in IoT
technologies and even Semantic Web technologies [3]. BMW is designing the Vehicle
Signal and Attribute (VSSO) ontology
5 [2] and the Vehicle Driving Context (VDC)
1 http://bit.ly/2xMZQDv.
2 https://gtnr.it/2SgUvOi.
3 http://bit.ly/2Y3A1xL.
4 http://www.bmwsummerschool.com/.
5 http://automotive.eurecom.fr/vsso.