Cognitive Framework of Food Quality Assessment in IoT-Inspired Smart Restaurants

Information and communication technology (ICT) empowered by the Internet of Things (IoT) and fog-cloud paradigm has been widely adopted in several domains of logistics, healthcare, and agriculture. Inspired by the enormous benefits of IoT technology, this research proposes a novel notion of smart restaurants for assessing the food quality using the game theory. Specifically, this research presents a smart framework for food quality assessment inside restaurants. Real-time data are acquired using numerous IoT devices for food quality assessment. The data are communicated to the fog nodes backed by the cloud platform. This enables the time-sensitive analysis of food quality for formalizing a quantifiable measure, i.e., food quality estimate (FQE) using the Bayesian modeling technique. FQE presents a quantification factor for assessing the food quality over temporal patterns in terms of the quality support index (QSI). This is followed by the 2-player game model for effective food quality assessment. The presented model is validated by deploying it over four data sets. Based on the comparative analysis with other decision-making techniques, the presented technique has registered superior performance in terms of temporal effectiveness, classification efficacy, statistical efficiency, and reliability.

Automated summary

This research proposes a novel concept of smart restaurants for assessing food quality using IoT and fog computing. Real-time data is used to quantify food quality using Bayesian modeling technique and assess it through a game model. The presented technique outperforms other decision-making techniques in terms of temporal effectiveness, classification efficacy, statistical efficiency, and reliability.