Application of fuzzy image processing and Iot real-time monitoring in sports training mode

Abstract

Abstract Blurred images are very complicated because imaging is affected by computer technology, sensor technology, vision, mathematics, environment, human activities, etc. Sometimes the available visual information is not what we can accept. The image sometimes has poor contrast, and due to different levels of damage, the sound or blind spots are also different. The Internet of Things has become the main focus of the industry. It can be considered as an extension of the three existing networks of Internet, telecommunications, and radio and television networks. And it gradually surpassed the interaction of people's information, and expanded to the information exchange between people and things, things and people, things and things. With the rapid development of the Internet of Things technology, especially the diversity of remote transmission methods and the improvement of the technical level, the remote real-time monitoring of the Internet of Things has been more and more widely used in the Internet. In the IoT monitoring system, the service is the bridge between data collection and data application. In order to improve the efficiency of the communication module and support the availability of multiple devices, it is very important to design an efficient communication server. Through real-time analysis of the exercise data brought by multiple students, personalized exercise training plans can be customized according to the different physiques of the students. It can be seen from the results of the simulation experiment that whether it is a separate analysis or an objective judgment, the test results show that the method in this paper is effective and it is possible to improve the image quality.