Abstract

Many methods of coffee roasting in the market today are only based on the temperature in the certain time period. However, if the coffee beans have no uniformity in size, weight, and moisture, the roasting process will not produce the consistent results. In this study, the measurement and identification of cracking sounds of coffee beans under roasting are applied to determine the temperature control mechanism. Roaster uses an oven-type controlled by heating element at a temperature of 260?C. In the roasting process, there are the first and second cracking sounds in the time span of 3-10 minutes. Voice Activity Detection is used to identify the cracking sound using Fast Fourier Transform to determine the starting point of sound recording. The data would be learned by the Neural Network to recognize the cracking sounds automatically. The Neural Network can obtain the best result during the period of 1-second recording with success rate of 100%.

Original languageEnglish
Title of host publication2017 International Seminar on Intelligent Technology and Its Application
Subtitle of host publicationStrengthening the Link Between University Research and Industry to Support ASEAN Energy Sector, ISITIA 2017 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages271-274
Number of pages4
ISBN (Electronic)9781538627068
DOIs
Publication statusPublished - 28 Nov 2017
Event18th International Seminar on Intelligent Technology and Its Application, ISITIA 2017 - Surabaya, Indonesia
Duration: 28 Aug 201729 Aug 2017

Publication series

Name2017 International Seminar on Intelligent Technology and Its Application: Strengthening the Link Between University Research and Industry to Support ASEAN Energy Sector, ISITIA 2017 - Proceeding
Volume2017-January

Conference

Conference18th International Seminar on Intelligent Technology and Its Application, ISITIA 2017
Country/TerritoryIndonesia
CitySurabaya
Period28/08/1729/08/17

Keywords

  • Coffee roasting
  • Cracking sound
  • Neural network

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