Electronic Nose using Convolutional Neural Network to Determine Adulterated Honeys

Abstract

Honey is a sweet and thick food substance that has high economic value which is often found in its adulteration. Impure honey frequently causes harm to people. Therefore, it requires a system that can assist in resolving the issue of adulterated honey. One method to deal with this issue is to use an electronic nose system. The system consists of gas sensors, a data acquisition circuit, and a pattern recognition algorithm. In this study, an electronic nose system comprised of an array of semiconductor gas sensors was built. Arduino microcontroller is used for data acquisition circuit. The pattern recognition algorithm uses the convolutional neural network (CNN) method. The experimental results show that this system recognizes honey with levels of 50%, 75%, 100%, and sugar with an accuracy rate of 100%.