Poster: Exploring the Need for Sensor Learning and Collaboration in IoT-based Parking Systems
Authors: 
Yu Huang, Dian-Xuan Wu, Chuang-Wen You, Chi-Ling Yang, Seng-Yong Lau, Kai-Lung Hua, Wen-Huang Cheng, Yi-Ling Chen, Jane Yung-Jen HsuAuthors Info & Claims
Pages 423 - 424
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.
References
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Accelerating sustainability: Demonstrating the benefits of transportation technology. http://digitalenergysolutions.org/dotAsset/933052fc-0c81--43cf-a061--6f76a44459d6.pdf.
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The learning curve of smart parking. http://www.nytimes.com/2012/12/23/technology/smart-parking-has-a-learning-curve-too.html.
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K. Blumer, H. R. Halaseh, M. U. Ahsan, H. Dong, and N. Mavridis. Cost-effective single-camera multi-car parking monitoring and vacancy detection towards real-world parking statistics and real-time reporting. In Proc. ICONIP 2012 - Volume Part V, pages 506--515. Springer-Verlag, 2012.
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C.-C. Chang and C.-J. Lin. Libsvm: A library for support vector machines. ACM Trans. Intell. Syst. Technol., 2(3):27:1--27:27, May 2011.
Index Terms
- Poster: Exploring the Need for Sensor Learning and Collaboration in IoT-based Parking Systems
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Information
Published In
November 2015
526 pages
ISBN:9781450336314
DOI:10.1145/2809695
- General Chair:
- Junehwa Song,
- Program Chairs:
- Tarek Abdelzaher,
- Cecilia Mascolo
Copyright © 2015 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
- SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
- SIGCOMM: ACM Special Interest Group on Data Communication
- SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
- SIGOPS: ACM Special Interest Group on Operating Systems
- SIGBED: ACM Special Interest Group on Embedded Systems
- SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 01 November 2015
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- Poster
Funding Sources
- National Taiwan University
- Intel Corporation
- Ministry of Science and Technology
Conference
SenSys '15: The 13th ACM Conference on Embedded Network Sensor Systems
November 1 - 4, 2015
Seoul, South Korea
Acceptance Rates
SenSys '15 Paper Acceptance Rate 27 of 132 submissions, 20%;
Overall Acceptance Rate 174 of 867 submissions, 20%
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