ParkMaster is a low-cost crowdsourcing architecture which exploits machine learning techniques and computer vision algorithms to evaluate parking availability in cities. While the user is normally driving, ParkMaster enables off the shelf smartphones to collect information about the presence of parked vehicles by running image recognition techniques on the phones camera video streaming.
NOTE Old project, not maintained anymore
@misc{grassi:hal-01231828,
TITLE = {{ParkMaster: Leveraging Edge Computing in Visual Analytics}},
AUTHOR = {Grassi, Giulio and Sammarco, Matteo and Bahl, Paramvir and Jamieson, Kyle and Pau, Giovanni},
URL = {https://hal.archives-ouvertes.fr/hal-01231828},
NOTE = {Poster},
HOWPUBLISHED = {{MobiCom'15 - 21st Annual International Conference on Mobile Computing and Networking}},
PUBLISHER = {{ACM}},
PAGES = {257-259},
YEAR = {2015},
MONTH = Sep,
DOI = {10.1145/2789168.2795174},
KEYWORDS = {Mobile sensors ; Vision Computing ; Cloudlet ; Crowdsourcing ; Design ; Edge Computing},
HAL_ID = {hal-01231828},
HAL_VERSION = {v1},
}