Cognitive Framework of Food Quality Assessment in IoT-Inspired Smart Restaurants
Munish Bhatia, Ankush Manocha
Abstract
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.