Paper Info
Title
Smap: A Map Extension Framework For Intelligent Travel Systems
Abstract
In the last few decades, special attention has been drawn to the autonomous vehicles and smart travel system in order to provide safer roads and a more comfortable driving experience. Acquiring knowledge about the locations type (home, work, shop, restaurant, etc.) and the possible pause time helps in transforming the vehicles into smart entities having similar road view as the human drivers. This understanding results subsequently in deriving more accurate destination predictions without the driver intervention and providing consequently more sophisticated high level applications. This paper proposes an Openstreetmap based framework (SMAP) for mining the significant locations serving as possible points of interest (POI). Moreover, it develops a semantic annotation technique to automatically annotate the POIs with category tags serving as a prerequisite for locations search and recommendation services. Furthermore, the work addresses the parking problem by assigning each POI a set of the nearest parking locations.
Year
DOI
Venue
2019
10.1109/ICCNC.2019.8685503
2019 INTERNATIONAL CONFERENCE ON COMPUTING, NETWORKING AND COMMUNICATIONS (ICNC)
Field
DocType
ISSN
Semantic annotation,Information retrieval,Computer science,SAFER,Point of interest
Conference
2325-2626
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Nardine Basta111.36
Amal El-nahas2416.47
Hans Peter Großmann3658.64
Slim Abdennadher439460.95