16 Citations (Scopus)

Abstract

Spoiled meat level can be detected manually by using the senses of sight and smell. However, it can endanger the human body if the gas emitted by rotting meat exhaled directly because of the bacterial contamination. Furthermore, such classifications are inevitably somewhat subjective since everyone has different assessments of the spoiled meat. This research presents the use of semiconductor gas sensors to detect gas emitting from rotting meat as a substitute for human olfaction. In addition, a camera equipped with image processing using Grey Level Co-Occurrence Matrix is applied as a replacement for vision. The responses of gas sensor array and Grey Level Co-occurrence Matrix were processed by Neural Network to classify the spoiled meat level. The classification of Artificial Neural Networks has a high percentage of success up to 82%. This method can replace the role of human senses in meat classification automatically.

Original languageEnglish
Title of host publication2018 International Conference on Information and Communications Technology, ICOIACT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages418-423
Number of pages6
ISBN (Electronic)9781538609545
DOIs
Publication statusPublished - 26 Apr 2018
Event1st International Conference on Information and Communications Technology, ICOIACT 2018 - Yogyakarta, Indonesia
Duration: 6 Mar 20187 Mar 2018

Publication series

Name2018 International Conference on Information and Communications Technology, ICOIACT 2018
Volume2018-January

Conference

Conference1st International Conference on Information and Communications Technology, ICOIACT 2018
Country/TerritoryIndonesia
CityYogyakarta
Period6/03/187/03/18

Keywords

  • Grey Level Co-occurrence Matrix
  • Neural Network
  • Semiconductor Gas Sensor
  • Spoiled Meat Level

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