Research on the strategy of teaching Internet of Things communication with base group intelligence algorithm in enhancing teaching interactivity

With the development of Internet of Things (IoT) technology, improving the interactivity of IoT communication teaching has become an important research content.This paper firstly constructs the IOT communication teaching system on the basis of service layer, network layer and teaching layer, through which the teaching information is ensured to be delivered timely and accurately.Secondly, the group intelligence algorithm teaching interactivity is optimized and designed to optimize the teaching environment, network, and teaching layer to get the optimized server resource allocation scheme to achieve the optimization of different levels in the teaching of Internet of Things communication.When the number of iterations reaches 20 and 45, the adaptability of this paper's algorithm is maintained between 100-10-1, and the optimization of the algorithm improves the student participation, the depth of understanding of knowledge, the accuracy of data, the speed of transmission, the efficiency of management, and the teaching effect by 28.6%, 41.7%, 4%, 100%, 18.8%, and 20%, respectively.In the delay analysis, when the number of terminals is 10, 20, and 30 respectively, the delay of the teaching system in this paper is the lowest among all the compared systems, which is 10ms, 40ms, and 230ms respectively.This study can lay the foundation for improving the quality and effect of IoT communication teaching and promote the cultivation of teaching interactivity between teachers and students.