Abstract

This research delves into the integration of the Internet of Things (IoT) into virtual communication platforms, specifically focusing on Augmented Reality (AR) applied to mechatronic systems. The primary goal is to explore how IoT and AR can synergize to improve communication efficiency and enhance user experience in mechatronic environments. Augmented Reality (AR) enables users to create and view virtual objects in physical 3D space. However, configuring AR technology, especially for displaying augmented information via QR codes on mobile devices, remains a challenge. The current research project addresses this by developing a framework for augmenting visual analytics and integrating it into mobile apps to provide dynamic representations. The analytics are sent to the Unity engine to embed them into the AR application. Tuning hyper parameters facilitates the examination of their impact on classification. Nine different classifiers, including J48 decision tree, Hoeffding tree, Random forest, Random Tree, REPTree, Bayes net, Naïve Bayes, OneR, and Decision table, are constructed and compared for optimal performance. The findings contribute to advancing the understanding of how IoT-assisted virtual communication on AR platforms can revolutionize mechatronic applications, fostering innovation and efficiency in this rapidly evolving field. The AR application utilizes predictive classification to enhance visualizations, and the OneR classifier, combined with monarch butterfly optimization, is recommended for the Walmart dataset due to its maximum accuracy of 92.3322% compared to other classifiers.