Moving vehicle identification using artificial neural network

International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.

Saved in:
Bibliographic Details
Main Authors: Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr., Abdul Hamid, Adom, Assoc. Prof. Dr., Siti Marhainis, Othman, Sundararaj, Sathish Kumar
Other Authors: paul@unimap.edu.my
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2012
Subjects:
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/20492
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimap-20492
record_format dspace
spelling my.unimap-204922012-07-19T13:09:55Z Moving vehicle identification using artificial neural network Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Abdul Hamid, Adom, Assoc. Prof. Dr. Siti Marhainis, Othman Sundararaj, Sathish Kumar paul@unimap.edu.my abdhamid@unimap.edu.my sathishy2j@yahoo.com Hearing impaired Backpropagation Multilayer Perceptron (MLP) Neural Network International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia. Hearing impaired people cannot distinguish the sound from a moving vehicle approaching from their behind. They often face a risky situation while they are in outdoors. In this paper, a simple algorithm is proposed to classify the type and distance of the moving vehicles based on the sound signature recorded from the vehicles. A simple experimental protocol is designed to record the vehicle sound under different environment conditions and velocity of vehicles. The noises emanated from moving vehicles along the roadside were recorded along with the type and distance of the vehicle. Autoregressive modeling algorithm is used for the analysis to extract features from the recorded sound signal. Two simple Multilayer Perceptron (MLP) models are developed and trained using Backpropagation algorithm to classify the vehicle type and its distance. The effectiveness of the network is validated through stimulation. 2012-07-19T13:09:54Z 2012-07-19T13:09:54Z 2012-02-27 Working Paper http://hdl.handle.net/123456789/20492 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2012) Universiti Malaysia Perlis (UniMAP) School of Mechatronic Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Hearing impaired
Backpropagation
Multilayer Perceptron (MLP) Neural Network
spellingShingle Hearing impaired
Backpropagation
Multilayer Perceptron (MLP) Neural Network
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Abdul Hamid, Adom, Assoc. Prof. Dr.
Siti Marhainis, Othman
Sundararaj, Sathish Kumar
Moving vehicle identification using artificial neural network
description International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.
author2 paul@unimap.edu.my
author_facet paul@unimap.edu.my
Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Abdul Hamid, Adom, Assoc. Prof. Dr.
Siti Marhainis, Othman
Sundararaj, Sathish Kumar
format Working Paper
author Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
Abdul Hamid, Adom, Assoc. Prof. Dr.
Siti Marhainis, Othman
Sundararaj, Sathish Kumar
author_sort Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
title Moving vehicle identification using artificial neural network
title_short Moving vehicle identification using artificial neural network
title_full Moving vehicle identification using artificial neural network
title_fullStr Moving vehicle identification using artificial neural network
title_full_unstemmed Moving vehicle identification using artificial neural network
title_sort moving vehicle identification using artificial neural network
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2012
url http://dspace.unimap.edu.my/xmlui/handle/123456789/20492
_version_ 1643793089018462208
score 13.214268