Fog computing-based intelligent inference performance evaluation system integrated internet of thing in food cold chain

The perishable and fresh products are one of the main drivers through food life cycle for consumer in today´s competitive environment. Cold chain literatures review are widely discussed to food safety and quality. In recent years, cold chain has centered on the consumer satisfaction for fresh food. Furthermore, it is special important for tourism food industry. Thence, this article proposes that three issues (tourism, cold technologies and traceability) are critical assessment factors for food product quality and safety using cold chain system in performance evaluation. No study has yet been published that considers the fog computing-based cold chain implicit to tourism-related food consumption. There are mainly two types of performance evaluation systems for cold chain network in Tourism, the T-S fuzzy inference and the fog computing based on ANN (artificial Neural networks) theory. The numerical example and experiments is discussed by utilizing different defuzzifier algorithm between T-S fuzzy and Best Non-fuzzy Performance Value (BNP).