Practical discrimination of good and bad cooked food using metal oxide semiconductor odour sensor

• Main Authors: Essiet Ima O., Dan-Isa Ado
• Format: Article
• Language: English
• Published: Faculty of Technology, Novi Sad 2013-01-01
• Series: Acta Periodica Technologica
• Subjects: neural network; ammonia; odour sensor; metal oxide semiconductor; electronic nose
• Online Access: http://www.doiserbia.nb.rs/img/doi/1450-7188/2013/1450-71881344039E.pdf

An increasing concentration of ammonia in cooked food is in direct proportion to the extent of decay. This fact is used to design an electronic nose (e-nose) based on metal oxide semiconductor odour sensor circuit capable of discriminating good and bad cooked food. On the basis of the data produced by the e-nose circuit, a feedforward multilayer neural network is designed and trained to recognize varying concentrations of ammonia in the food. Test results of the prototype e-nose system show that it is capable of classifying cooked food as being good or bad with over 92% average success rate.