Meat is one of foodstuff that widely consumed in the world. Unfortunately, the quality of meat can easily degrade if not handled properly and become the serious health hazards if consumed. Hence, the food safety system is very important to guarantee the quality of food to be consumed. In this study, we introduced the development of mobile electronic nose for beef quality detection and monitoring. This system is developed using low-cost hardware and possible to integrate with cooling box or refrigerator for real time monitoring and analysis during distribution and storage processes. K-Nearest Neighbor with signal preprocessing is used to classify two, three, and four classes of beef. The experimental results show that the system can perfectly distinguish fresh and spoiled beef. Moreover, it has promising classification accuracy for binary, three classes, and four classes classification with 93.64%, 86.00%, and 85.50%, respectively. Hence, this system has a potential solution to provide low-cost, easy to use, and real-time meat quality monitoring system.

Original languageEnglish
Pages (from-to)728-735
Number of pages8
JournalProcedia Computer Science
Publication statusPublished - 2017
Event4th Information Systems International Conference 2017, ISICO 2017 - Bali, Indonesia
Duration: 6 Nov 20178 Nov 2017


  • Beef Quality Monitoring
  • Classification
  • K-Nearest Neighbor
  • Mobile Electronic Nose


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