Detection and classification of bacteria in common street foods using electronic nose and support vector machine

Abstract

Street food has a major impact on the culture and lifestyle of Filipinos, but because of the lack of knowledge in proper food preparation, the cleanliness and quality of street food is neglected. Bad bacteria that causes diarrheal diseases lives on it, and it is hard to detect whether the bacteria are present, without an instrument like an electronic nose, and image processing. This paper aims to design an electronic nose with gas sensors that will detect three common types of bacteria on street foods namely Enterococcus faecalis, Escherichia coli and Staphylococcus aureus; and to classify if the said bacteria are present in the pre-cooking stage and which bacteria are still present after cooking. Electronic nose system detects the bacteria in the sample street food during pre-cooking stage and Support Vector Machine detects the bacteria in the sample street food during post-cooking stage.