Design of an iota tangle-based intelligent food safety service platform for bubble tea

Abstract

Many food safety incidents have occurred in the world in the past 20 years, causing major threats and harm to human life and health. Each country or region has established different food safety management systems (FSMSs) in response, to increase food safety and to reduce food safety risks. Hence, it is important to develop an FSMS service platform with convenience, consistency, effectiveness, scalability, and lightweight computing. The aim of this study is to design and pro-pose an IOTA Tangle-based intelligent food safety service platform for bubble tea—called IF4BT—which modularizes and integrates hazard analysis and critical control point (HACCP) principles to increase data transparency. The deep learning inference engine is based on long short-term memory and Siamese networks to check and extract significant rare data of high-risk factors, exception factors, and noises, depending on daily check and audit. IF4BT can ensure the correctness of the information of food manufacturers, so as to increase food safety and to reduce food safety issues such as allergen cross-contamination, food expiration, food defense, and food fraud.