Autonomous tracing system for backward design in food supply chain

• Published in: Food control Vol. 51; pp. 70 - 84
• Main Author: Chen, Rui-Yang
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.05.2015
• Subjects: Food supply chain; Fuzzy cognitive maps; Fuzzy rule; Internet of things; Internet of things; Fuzzy rule; Fuzzy cognitive maps; Food supply chain
• ISSN: 0956-7135; 1873-7129
• DOI: 10.1016/j.foodcont.2014.11.004

Food safety and quality issues generally occur due to incurring problem of food products handling processing. It led to a growing interest in developing systems for food supply chain traceability. At present, there are lacking in modeling the traceability process for developing “autonomous” traceability system in comparative to “automation” and little research has been conducted where the product problem information related to the cause of problem, the responsibility attribution simultaneously. This paper design the autonomous agent-based tracing system based on IoT (internet of things) architecture using FCM (fuzzy cognitive maps) and fuzzy rule method for product usage life cycle. The case study for agriculture food product is discussed. It aimed to simulating food tracing complex system with imprecise relationships while quantifying the performance impact of backward design process efficiency using the total effects algorithm. •The autonomous IoT-agent-based tracing system uses FCM and fuzzy rule method.•This paper describes an integrated framework of IoT-based product usage life cycle.•An object-oriented relational database link traceability in class hierarchy diagram.•The ATFCM of the impact of food product problem tracing system can be effective.•The F1-metric and total effects algorithm shows on benefits of traceability FSC.