Intelligent decision-making in Smart Food Industry: Quality perspective

Fog-Cloud computing empowered Internet of Things (IoT) technology has conceptualized the ideology of Industry 4.0. Inspired by this, the food industry 4.0 presents a unique concept for determining food quality in real-time. Conspicuously, the current research provides an IoT-based smart framework for evaluating the food-quality parameters in restaurants and food outlets. IoT technology is primarily utilized to gather data that can explicitly affect food quality within a food serving environment. Such data is analyzed using the Bayesian Modeling Technique on the Fog-Cloud platform to derive a unanimous metric in terms of Probability of Food Grade (PoFG). Also, Food Grade Assessment Scale (FGAS) is quantified to assess real-time food-oriented parameters in the ambient environment of food-outlets and restaurants. Furthermore, a 2-player game theoretic model is proposed for food quality-oriented decision services by monitoring officials and food managers. For evaluation purposes, the presented model is deployed over a challenging dataset comprising of nearly 42,410 instances. The comparative simulations were carried out with state-of-the-art methodologies, which demonstrated the dominance of the presented model in terms of Data assessment efficacy, Statistical classification analysis, Decision-making efficiency, Reliability, and Stability. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

This study presents an IoT-based smart framework for evaluating food quality parameters in restaurants and food outlets. Utilizing Bayesian Modeling Technique and the Food Grade Assessment Scale (FGAS), real-time assessment of food quality is achieved. A 2-player game theoretic model is proposed for decision services by monitoring officials and food managers.