@inproceedings{1b50297cec2d4c50bfe6a13746e1a7de,
title = "Poster: Exploring the need for sensor learning and collaboration in IoT-based parking systems",
abstract = "The need to find parking contributes to road congestion and leads to unnecessary fuel consumption. Of all emerging parking systems, Internet-of-Things (IoT)-based systems have demonstrated the feasibility of real-time delivery of parking availability using magnetic sensors. However, existing magnetic-based methods are prone to false positives caused by electromagnetic fields emitted from surrounding electric facilities. In this study, we conducted a 3-month data collection in a parking area. We identified the need to introduce learning and collaboration into the design of our detection algorithm which recognizes learned patterns associated with car arrivals or departures, and to filter out unreliable events based on spatial and temporal features.",
keywords = "Internet of Things (IoT), Magnetic sensing, Smart parking",
author = "Yu Huang and Wu, {Dian Xuan} and You, {Chuang Wen} and Yang, {Chi Ling} and Lau, {Seng Yong} and Hua, {Kai Lung} and Cheng, {Wen Huang} and Chen, {Yi Ling} and Hsu, {Jane Yung Jen}",
year = "2015",
month = nov,
day = "1",
doi = "10.1145/2809695.2817895",
language = "英语",
series = "SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems",
publisher = "Association for Computing Machinery, Inc",
pages = "423--424",
booktitle = "SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems",
note = "13th ACM Conference on Embedded Networked Sensor Systems, SenSys 2015 ; Conference date: 01-11-2015 Through 04-11-2015",
}