Internet of Things (IoT) is defined as the interconnection of millions of wireless devices to acquire data in a ubiquitous manner. With multiple devices targeting to perceive data over a common platform, it becomes indispensable to analyze accuracy for realizing an optimal IoT environment. Inspired from these aspects, this study presents a novel Quantum Computing-inspired (IoT-QCiO) optimization technique to maximize data accuracy in a real-time environment of IoT application. Specifically, the presented model incorporates quantum formalization of sensor-specific parameters to quantify IoT devices in terms of Sensors in Vicinity (SIV) and Optimal Sensor Space (OSS). The optimality of the presented algorithm is estimated in terms of 3 key performance indicators of Data Cost (DC), Data Accuracy (DA) and Data Temporal Efficiency (DTE). For validation purposes, the proposed algorithm is implemented for monitoring geographical traffic to address vehicular routing problems using 90 WiSense nodes, Raspberry Pi v3, and Quantum Simulators. Results obtained were compared with several state-of-the-art optimization algorithms. Based on the results, significant improvement was registered for the proposed model in terms of statistical parameters of Precision, Sensitivity, Specificity, F-measure. Moreover, enhanced values of reliability depict the optimal performance of the proposed approach.

Recently, there has been a substantial amount of research on smart classrooms, encompassing a number of areas, including Information and Communication Technology, Machine Learning, Sensor Networks, Cloud Computing, and Hardware. Smart classroom research has been quickly implemented to enhance education systems, resulting in higher engagement and empowerment of students, educators, and administrators. Despite decades of using emerging technology to improve teaching practices, critics often point out that methods miss adequate theoretical and technical foundations. As a result, there have been a number of conflicting reviews on different perspectives of smart classrooms. For a realistic smart classroom approach, a piecemeal implementation is insufficient. This survey contributes to the current literature by presenting a comprehensive analysis of various disciplines using a standard terminology and taxonomy. This multi-field study reveals new research possibilities and problems that must be tackled in order to integrate interdisciplinary works in a synergic manner. Our analysis shows that smart classroom is a rapidly developing research area that complements a number of emerging technologies. Moreover, this paper also describes the co-occurrence network of technological keywords using VOSviewer for an in-depth analysis.