Abstract
Reliable and accurate traffic sensing is the basis of Intelligent Transportation Systems (ITS), which mitigate traffic mobility and safety issues. To promote vast adoption of ITS technologies, rapid deployment and auto-calibration of traffic sensing systems are critical. Aiming at the development of an advanced traffic sensing system for construction zones, this poster presents our preliminary results for detecting vehicles and estimating traffic speeds by applying signal processing and machine learning techniques using Passive Infrared (PIR) sensor data.
Original language | English (US) |
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Title of host publication | IPSN 2015 - Proceedings of the 14th International Symposium on Information Processing in Sensor Networks (Part of CPS Week) |
Publisher | Association for Computing Machinery, Inc |
Pages | 370-371 |
Number of pages | 2 |
ISBN (Electronic) | 9781450334754 |
DOIs | |
State | Published - Apr 13 2015 |
Event | 14th International Symposium on Information Processing in Sensor Networks, IPSN 2015 - Seattle, United States Duration: Apr 13 2015 → Apr 16 2015 |
Publication series
Name | IPSN 2015 - Proceedings of the 14th International Symposium on Information Processing in Sensor Networks (Part of CPS Week) |
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Conference
Conference | 14th International Symposium on Information Processing in Sensor Networks, IPSN 2015 |
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Country/Territory | United States |
City | Seattle |
Period | 04/13/15 → 04/16/15 |
Bibliographical note
Publisher Copyright:Copyright 2015 ACM.
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
- Computer Networks and Communications