Authors - Rydhm Beri, Parul Sachdeva Abstract - The advent of IoT technology has significantly transformed the industrial sector, paving the way for the emergence of Food Industry 4.0. This research explores the integration of edge–cloud computing and IoT to create a smart framework tailored for the food industry. Central to this framework is the appli-cation of a Bayesian belief network (BBN) on an edge–cloud platform, enabling data-driven insights into food quality. The framework assesses data to calculate the Probability of Food Quality (PFQ) and utilizes the Food Quality Analysis Measure (FQAM) to evaluate food outlets. A bi-level decision-tree model further enhances the evaluation process by providing an in-depth analysis of food quality metrics. To address concerns around data security, blockchain technology is implemented, ensuring the protection of food-related information. The model is rigorously tested on a comprehensive dataset encompassing 43,520 instances from four restaurants. Simulation results highlight its high performance, achieving a temporal delay of 96.43 seconds, and the system demonstrates an accuracy of 98.93%, showcasing its robustness in real-world applications.
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