MOCUS : moving object counting using ultrasonic sensor networks

Quanbin CHEN*, Min GAO, Jian MA, Dian ZHANG, Lionel M. NI, Yunhao LIU

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)Researchpeer-review

14 Citations (Scopus)

Abstract

Counting the number of moving objects in a given area has many practical applications. By investigating a series of state-of-the-art technologies, we propose a Moving Object Counting approach using Ultrasonic Sensor networks (MOCUS). In MOCUS, we deploy a network of three-node ultrasound sensor clusters, with each cluster having one ultrasound transmitting node and two ultrasound receiving nodes. Such three-node sensor clusters can successfully offset interference problems and accurately detect the direction of moving objects. In order to cover a wide area, MOCUS employs multiple sensor clusters, forming a wireless sensor network. To alleviate the impact of object moving velocity, shape of objects and distinguish closely tied multiple objects, we introduce intra-cluster analysis and inter-cluster cooperation techniques. We deploy a MOCUS prototype in our lab and evaluate the design through extensive experiments.
Original languageEnglish
Pages (from-to)55-65
Number of pages11
JournalInternational Journal of Sensor Networks
Volume3
Issue number1
Early online date30 Dec 2007
Publication statusPublished - 2008
Externally publishedYes

Fingerprint

Ultrasonic sensors
Sensor networks
Ultrasonics
Sensors
Cluster analysis
Sensor nodes
Wireless sensor networks
Experiments

Keywords

  • moving object counting
  • wireless sensor networks
  • ultrasound
  • clustering

Cite this

CHEN, Quanbin ; GAO, Min ; MA, Jian ; ZHANG, Dian ; NI, Lionel M. ; LIU, Yunhao. / MOCUS : moving object counting using ultrasonic sensor networks. In: International Journal of Sensor Networks. 2008 ; Vol. 3, No. 1. pp. 55-65.
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CHEN, Q, GAO, M, MA, J, ZHANG, D, NI, LM & LIU, Y 2008, 'MOCUS : moving object counting using ultrasonic sensor networks', International Journal of Sensor Networks, vol. 3, no. 1, pp. 55-65.

MOCUS : moving object counting using ultrasonic sensor networks. / CHEN, Quanbin; GAO, Min; MA, Jian; ZHANG, Dian; NI, Lionel M.; LIU, Yunhao.

In: International Journal of Sensor Networks, Vol. 3, No. 1, 2008, p. 55-65.

Research output: Journal PublicationsJournal Article (refereed)Researchpeer-review

TY - JOUR

T1 - MOCUS : moving object counting using ultrasonic sensor networks

AU - CHEN, Quanbin

AU - GAO, Min

AU - MA, Jian

AU - ZHANG, Dian

AU - NI, Lionel M.

AU - LIU, Yunhao

PY - 2008

Y1 - 2008

N2 - Counting the number of moving objects in a given area has many practical applications. By investigating a series of state-of-the-art technologies, we propose a Moving Object Counting approach using Ultrasonic Sensor networks (MOCUS). In MOCUS, we deploy a network of three-node ultrasound sensor clusters, with each cluster having one ultrasound transmitting node and two ultrasound receiving nodes. Such three-node sensor clusters can successfully offset interference problems and accurately detect the direction of moving objects. In order to cover a wide area, MOCUS employs multiple sensor clusters, forming a wireless sensor network. To alleviate the impact of object moving velocity, shape of objects and distinguish closely tied multiple objects, we introduce intra-cluster analysis and inter-cluster cooperation techniques. We deploy a MOCUS prototype in our lab and evaluate the design through extensive experiments.

AB - Counting the number of moving objects in a given area has many practical applications. By investigating a series of state-of-the-art technologies, we propose a Moving Object Counting approach using Ultrasonic Sensor networks (MOCUS). In MOCUS, we deploy a network of three-node ultrasound sensor clusters, with each cluster having one ultrasound transmitting node and two ultrasound receiving nodes. Such three-node sensor clusters can successfully offset interference problems and accurately detect the direction of moving objects. In order to cover a wide area, MOCUS employs multiple sensor clusters, forming a wireless sensor network. To alleviate the impact of object moving velocity, shape of objects and distinguish closely tied multiple objects, we introduce intra-cluster analysis and inter-cluster cooperation techniques. We deploy a MOCUS prototype in our lab and evaluate the design through extensive experiments.

KW - moving object counting

KW - wireless sensor networks

KW - ultrasound

KW - clustering

M3 - Journal Article (refereed)

VL - 3

SP - 55

EP - 65

JO - International Journal of Sensor Networks

JF - International Journal of Sensor Networks

SN - 1748-1279

IS - 1

ER -