The Classroom Education Model of Artificial Intelligence and Information Technology Supported by Wireless Networks

Abstract

Multimodal is one of the methods of teaching or ideas formed from a different set of models and teaching content to enhance the student's experience in their field of study. This method can be implemented in various scenarios, such as video lessons, interactive elements, and a list of questions. Teachers should have enough ideas to cover students in all the categories. The students have to listen to the courses through an online learning platform or a live session. This proposed work focuses on multimodal teaching and learning concepts combined with wireless sensor networks and AI. Additionally, the implementation of technology in classroom education is being done to handle the multimodal data. This idea is implemented with the Random Offloading Algorithm which works based on the multiagent system. This multiagent system is implemented for optimizing the user's response delay and hence balancing the effective resource allocation of the server. The main role of this Random Offloading Algorithm in the proposed system is to focus on the online classes for the students through wireless network and to make effective response to the student's queries. The proposed system is later compared with the existing ANN classification model. The results show that the proposed algorithm has provided 98.99% accuracy in providing better classroom education.