Abstract
With the continuous development of computer technology and the gradual popularization of information technology application, the construction of intelligent teaching scene based on wireless sensing technology plays a more and more important role in modern information education. Taking a primary school as an example, this paper introduces multimodal wireless sensing technology into the construction of intelligent teaching system. The purpose of this paper is to explore the construction of a new teaching scene. Firstly, this paper deeply analyzes the sensing mechanism of wireless signal and optimizes the sensing mode, deployment structure, and signal processing in practical application, so that the system can run more effectively in the actual environment. Then, based on multimodal wireless sensing technology, this paper designs and optimizes the basic architecture and functions of intelligent teaching scene. The results show that combining the characteristic information of each mode to get the information conducive to identity confirmation, which can get better recognition performance and improve the accuracy. Combining the information of multiple modes can greatly improve the recognition performance. The user interest model combined with dynamic and static is used to optimize the system recommended resources, so that students can obtain high-quality and highly matched learning resources more quickly and accurately, so as to improve students’ learning efficiency in resource acquisition.
Highlights
Wireless signals can be used to transmit data and to sense the environment
More and more scientific and technological researchers have focused on wireless sensing technology, which has made great progress
Liu et al [16] realized wireless sensing by using the propagation time information of wireless network signals
Summary
Wireless signals can be used to transmit data and to sense the environment. There have been indoor radar systems using ultrawideband signals These technologies rely on specially designed signals or hardware equipment to obtain higher time resolution and more accurate ranging. Multimodal face recognition technology can extract the feature information of face images from different modes at the same time and combine the feature information of each mode to get the information conducive to identity confirmation In this way, it can get better recognition performance and improve accuracy [9]. Multimodal image fusion technology can obtain unified information through different processing methods (space-frequency conversion, feature extraction, or decision-making level judgment) from multiple information of the same object collected by multiple sensors, so as to obtain richer, more accurate, and more reliable information. That students can more quickly and accurately obtain high-quality and highly matched learning resources, so as to improve students’ learning efficiency in resource acquisition
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