Image extraction and data collection for solid waste bin monitoring system

Hannan M A, W. Zailah

Research output: Contribution to journalArticle

Abstract

This paper deals with the image extraction and data collection for solid waste monitoring and management system using the integration of information and communication technologies. The image sensor is used in this system using quarter video graphic array red green blue (QVGA RGB) camera for processing and analysing graphical of the waste bin status and image data is collected by the server parses from GPRS and GIS network. An artificial neural network approach has beenused to extract the image feature for further analysis to classify images of the waste bin level. The system has been successfully designated with the motivation of waste bin monitoring system, to escalate the results that can applied to wide variety of local municipal authorities system.

Original languageEnglish
Pages (from-to)3908-3913
Number of pages6
JournalJournal of Applied Sciences Research
Volume8
Issue number8
Publication statusPublished - 2012
Externally publishedYes

Fingerprint

Bins
Solid wastes
Monitoring
Image sensors
Geographic information systems
Servers
Cameras
Neural networks
Communication
Processing

Keywords

  • GIS
  • GSM
  • Management
  • RFID
  • Solid waste truck monitoring

ASJC Scopus subject areas

  • General

Cite this

Image extraction and data collection for solid waste bin monitoring system. / M A, Hannan; Zailah, W.

In: Journal of Applied Sciences Research, Vol. 8, No. 8, 2012, p. 3908-3913.

Research output: Contribution to journalArticle

@article{382bdd08e9b54927b4ba861a83dcba77,
title = "Image extraction and data collection for solid waste bin monitoring system",
abstract = "This paper deals with the image extraction and data collection for solid waste monitoring and management system using the integration of information and communication technologies. The image sensor is used in this system using quarter video graphic array red green blue (QVGA RGB) camera for processing and analysing graphical of the waste bin status and image data is collected by the server parses from GPRS and GIS network. An artificial neural network approach has beenused to extract the image feature for further analysis to classify images of the waste bin level. The system has been successfully designated with the motivation of waste bin monitoring system, to escalate the results that can applied to wide variety of local municipal authorities system.",
keywords = "GIS, GSM, Management, RFID, Solid waste truck monitoring",
author = "{M A}, Hannan and W. Zailah",
year = "2012",
language = "English",
volume = "8",
pages = "3908--3913",
journal = "Journal of Applied Sciences Research",
issn = "1816-157X",
publisher = "INSInet Publications",
number = "8",

}

TY - JOUR

T1 - Image extraction and data collection for solid waste bin monitoring system

AU - M A, Hannan

AU - Zailah, W.

PY - 2012

Y1 - 2012

N2 - This paper deals with the image extraction and data collection for solid waste monitoring and management system using the integration of information and communication technologies. The image sensor is used in this system using quarter video graphic array red green blue (QVGA RGB) camera for processing and analysing graphical of the waste bin status and image data is collected by the server parses from GPRS and GIS network. An artificial neural network approach has beenused to extract the image feature for further analysis to classify images of the waste bin level. The system has been successfully designated with the motivation of waste bin monitoring system, to escalate the results that can applied to wide variety of local municipal authorities system.

AB - This paper deals with the image extraction and data collection for solid waste monitoring and management system using the integration of information and communication technologies. The image sensor is used in this system using quarter video graphic array red green blue (QVGA RGB) camera for processing and analysing graphical of the waste bin status and image data is collected by the server parses from GPRS and GIS network. An artificial neural network approach has beenused to extract the image feature for further analysis to classify images of the waste bin level. The system has been successfully designated with the motivation of waste bin monitoring system, to escalate the results that can applied to wide variety of local municipal authorities system.

KW - GIS

KW - GSM

KW - Management

KW - RFID

KW - Solid waste truck monitoring

UR - http://www.scopus.com/inward/record.url?scp=84872526211&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84872526211&partnerID=8YFLogxK

M3 - Article

VL - 8

SP - 3908

EP - 3913

JO - Journal of Applied Sciences Research

JF - Journal of Applied Sciences Research

SN - 1816-157X

IS - 8

ER -