Neural net device for IED gas identification Kennedy, Robert and Nahavandi, Saeid 2010, Neural net device for IED gas identification, in ISIEA 2010 : 2010 IEEE Symposium on Industrial Electronics and Applications, IEEE, Piscataway, N.J., pp. 727-732. Attached Files Name Description MIMEType Size Downloads nahavandi-neuralnet-2010.pdf Published version application/pdf 1.16MB 250 Title Neural net device for IED gas identification Author(s) Kennedy, Robert Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name IEEE Symposium on Industrial Electronics and Applications (3rd : 2010 : Penang, Malaysia) Conference location Penang, Malaysia Conference dates 3-5 Oct. 2010 Title of proceedings ISIEA 2010 : 2010 IEEE Symposium on Industrial Electronics and Applications Editor(s) [Seroji, Mohd Nawawi ] Publication date 2010 Conference series IEEE Symposium on Industrial Electronics and Applications Start page 727 End page 732 Total pages 6 Publisher IEEE Place of publication Piscataway, N.J. Keyword(s) gas sensing artificial neural net embedded Summary Most of the embedded systems that detect gases today are for specific types and indicate the levels of the gas present with their standard sensors. We introduce here an adaptable system that can detect and distinguish the type of gas in a volatile environment such as searching for Improvised Explosive Devices (IEDs). This is achieved with a small device mounted on a mobile robot through the use of an algorithm that is an Artificial Neural Network (ANN). The input layer to the ANN is an array of environmental and gas sensors. The small device, comprising of a multilayer circuit board with sensors in a rugged lightweight case, mounts on the mobile robot and communicates the gaseous data to the robot. The ANN is implemented in the hardware of a FPGA with the control of the ANN being achieved through the configurable processor and memory. Calibration and testing of the device involves the training of device and the ANN with specific target gases. The Accuracy of the device is validated through lab testing against high-end gas test instruments with known concentrations of gases. Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder ISBN 9781424476473 Language eng Field of Research 090609 Signal Processing Socio Economic Objective 810104 Emerging Defence Technologies HERDC Research category E1 Full written paper - refereed HERDC collection year 2010 Copyright notice ©2010, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30034533 Document type: Conference Paper Collections: Centre for Intelligent Systems Research Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Mon, 09 May 2011, 19:39:22 EST Mon, 23 May 2011, 13:52:16 EST Tue, 24 May 2011, 14:49:57 EST Tue, 24 May 2011, 14:51:09 EST Tue, 24 May 2011, 14:57:03 EST Tue, 24 May 2011, 14:58:47 EST Tue, 24 May 2011, 14:59:55 EST Tue, 24 May 2011, 15:01:05 EST Tue, 24 May 2011, 15:06:50 EST Thu, 02 Jun 2011, 13:36:51 EST Fri, 16 Mar 2012, 18:54:52 EST Fri, 24 Jan 2014, 10:08:13 EST Wed, 21 Oct 2015, 14:01:16 EST Tue, 06 Sep 2016, 17:02:21 EST Tue, 05 Dec 2017, 10:49:46 EST Fri, 07 Sep 2018, 15:25:06 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 495 Abstract Views, 260 File Downloads  -  Detailed Statistics Created: Mon, 09 May 2011, 19:39:11 EST by Sandra Dunoon

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.