@inproceedings{7f10c363b1904e84b0225f3ce26b4c5f,
title = "ParkMaster - Leveraging edge computing in visual analytics",
abstract = "In this work we propose ParkMaster, a low-cost crowdsourcing architecture which exploits machine learning techniques and 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. The paper describes the design of ParkMaster's architecture and shows the feasibility of deploying such mobile sensor system in nowadays smartphones, in particular focusing on the practicability of running vision algorithms on phones.",
keywords = "Cloudlet, Crowdsourcing, Design, Edge computing, Mobile sensors, Vision computing",
author = "Giulio Grassi and Matteo Sammarco and Paramvir Bahl and Kyle Jamieson and Giovanni Pau",
year = "2015",
month = sep,
day = "7",
doi = "10.1145/2789168.2795174",
language = "English (US)",
series = "Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM",
publisher = "Association for Computing Machinery",
pages = "257--259",
booktitle = "MobiCom 2015 - Proceedings of the 21st Annual International Conference on Mobile Computing and Networking",
note = "21st Annual International Conference on Mobile Computing and Networking, MobiCom 2015 ; Conference date: 07-09-2015 Through 11-09-2015",
}