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Towards continuous surveillance of fruit flies using sensor networks and machine vision

Liu, Yuee, Zhang, Jinglan, Richards, Mark A., Pham, Binh L., Roe, Paul, & Clarke, Anthony R. (2009) Towards continuous surveillance of fruit flies using sensor networks and machine vision. In The 5th International Conference on Wireless Communications, Networking and Mobile Computing, 24-26 September 2009, Beijing.

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Abstract

In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

Impact and interest:

2 citations in Scopus
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1 citations in Web of Science®

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282 since deposited on 14 Oct 2009
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ID Code: 27940
Item Type: Conference Paper
Keywords: fruit fly monitoring, machine vision, sensor networks
ISBN: 9781424436934
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2009 IEEE
Copyright Statement: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.
Deposited On: 14 Oct 2009 13:23
Last Modified: 01 Mar 2012 00:06

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