Modeling and evaluation on WSN-enabled and knowledge-based HACCP quality control for frozen shellfish cold chain

Abstract

Shellfish have limited shelf life due to quality fluctuation caused by biochemical, microbiological or physical changes under real cold chain conditions. The objective of this study was to integrate Wireless Sensors Network (WSN) monitoring system and knowledge engineering to monitor the dynamic indicators that affect quality characteristics and establish knowledge-based HACCP quality control plan to improve the safety of frozen shellfish in the real cold chain. The obtained dynamic data by WSN including temperature, humidity, O2, CO2 indicators, and an Arrhenius equation based kinetic model were simulated with field cold chain scenarios to determine the shelf life and quality loss probability. The key quality control points were identified based on the HACCP plan and unified representation and reasoning rule were established for enhancing the HACCP knowledge sharing and reuse. The system was tested and evaluated in cold chain logistics from Rushan to Fuzhou, China. The results show WSN-based monitoring can achieve the dynamic indicators continuous monitoring and contribute to the CCPs dynamic adjustment. The application of WSN-enabled and knowledge-based HACCP modeling as effective approach can help to increase cold chain management (CCM) transparency and improve the quality control for the frozen shellfish during their commercial life.