Fuzzy logic-based barcode scanning system for food products halal identification

Abstract

Halal status in food products is fundamental for Muslims and may be crucial for those who are allergic to non-halal ingredients when choosing suitable foods for consumption. However, with the rising demand for food products and the advancement of science and technology, contamination with non-halal substances is likely to occur in food production. Furthermore, some irresponsible food industry players tend to replace halal with non-halal ingredients to reduce costs. Therefore, it is crucial to identify the contents of halal food products to ensure compliance with the guidelines outlined by the Department of Islamic Development Malaysia (JAKIM). In this study, an integrated fuzzy logic barcode scanning system was developed to determine non-halal ingredients and traces in packaged food products. Although the information on food products can be easily accessed from the open-source web data bank, using the proposed fuzzy logic based-barcode scanning system to identify the authenticity of halal food products is an alternative option for providing accurate, reliable, and fast detection. The inputs for the fuzzy logic framework are halal logo, alcohol, animal fats, gelatin, ham, bacon, L-cysteine, lipase, mono-and diglycerides, pepsin, rennet, sodium stearoyl lactylate, vanilla extract, whey, and E-code of E120, E422, E441, E470, E542, and E904. On the other hand, the outputs are halal, uncertain, and non-halal. The fuzzy logic-based barcode system was able to identify the halal status for three different categories: samples with a halal logo, uncertain halal status samples, and non-halal samples.