TY - GEN
T1 - Vehicle detection and speed estimation with PIR sensors
AU - Donovan, Brian
AU - Li, Yanning
AU - Stern, Raphael
AU - Jiang, Jiming
AU - Claudel, Christian
AU - Work, Daniel
N1 - KAUST Repository Item: Exported on 2021-12-14
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/670525
UR - http://dl.acm.org/citation.cfm?doid=2737095.2742918
UR - http://www.scopus.com/inward/record.url?scp=84954094958&partnerID=8YFLogxK
U2 - 10.1145/2737095.2742918
DO - 10.1145/2737095.2742918
M3 - Conference contribution
AN - SCOPUS:84954094958
SN - 9781450334754
SP - 370
EP - 371
BT - Proceedings of the 14th International Conference on Information Processing in Sensor Networks
PB - ACM Press
ER -