Research Article
Pedestrian network data collection through location-based social networks
@INPROCEEDINGS{10.4108/ICST.COLLABORATECOM2009.8388, author={Piyawan Kasemsuppakorn and Hassan A. Karimi}, title={Pedestrian network data collection through location-based social networks}, proceedings={5th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing}, proceedings_a={COLLABORATECOM}, year={2009}, month={12}, keywords={Pedestrian Network Collaborative Mapping Social Network Location-Awareness Mobility}, doi={10.4108/ICST.COLLABORATECOM2009.8388} }
- Piyawan Kasemsuppakorn
Hassan A. Karimi
Year: 2009
Pedestrian network data collection through location-based social networks
COLLABORATECOM
ICST
DOI: 10.4108/ICST.COLLABORATECOM2009.8388
Abstract
The increasing capabilities of mobile devices and their mobile positioning technologies have shown great promise in location-enabled applications such as navigation systems. One of the essential components of a navigation system is a spatial database as it provides the base data to perform navigation and routing functions, among others. With the popularity of vehicle navigation systems, road network databases are now well developed and well suited for vehicles traveling on roads. However, road networks are not suitable for pedestrian navigation systems as pedestrians do not walk along the middle of street lanes and are not constrained by the boundaries of the road. Consequently, pedestrian network data is needed in location-enabled applications for pedestrians and other applications including transportation planning and physical activities study. Due to the lack of availability of pedestrian network data, new approaches for acquiring and maintaining pedestrian network data that are efficient and cost effective are needed. This paper presents a new approach that is based on location-based social networking for collecting pedestrian network data. The proposed approach stems from the concept of collaborative mapping where pedestrian network data can be collected by members of a social network recording GPS trajectories. A prototype based on a framework called Social Navigation Network (SoNavNet) for sharing and recommending navigation related information is also discussed.