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.

启用雾云计算的物联网（IoT）技术已经概念化了工业4.0的思想。受此启发，食品工业4.0提出了独特的概念，可实时确定食品质量。值得注意的是，当前的研究提供了一种基于物联网的智能框架，用于评估餐馆和食品商店的食品质量参数。物联网技术主要用于收集可以显着影响食品服务环境中食品质量的数据。在Fog-Cloud平台上使用贝叶斯建模技术对此类数据进行分析，以得出食品级概率（PoFG）的一致指标。此外，对食品等级评估量表（FGAS）进行了量化，以评估食品商店和饭店周围环境中的实时食品导向参数。此外，通过监视官员和食品经理，提出了一种针对食品质量的决策服务的两人博弈论模型。出于评估目的，将提出的模型部署在包含近42,410个实例的具有挑战性的数据集上。使用最先进的方法进行了比较模拟，这些方法从数据评估效力，统计分类分析，决策效率，可靠性和稳定性方面证明了所提出模型的优势。