{"title":"Wearable Optical Imaging Devices Based on Wireless Sensor Networks and Fuzzy Image Restoration Algorithms for Sports Image Analysis","authors":"Linyan Li","doi":"10.1007/s11036-024-02405-w","DOIUrl":null,"url":null,"abstract":"<p>With the rapid development of Internet of Things technology, wearable optical imaging devices can monitor the status and performance of athletes in real time, but the image quality is affected by environmental factors, often resulting in information loss. This study aims to improve the effectiveness of wearable optical imaging devices in sports image analysis by using wireless sensor networks and fuzzy image recovery algorithms, so as to achieve more accurate motion state monitoring. Wireless sensor network architecture combined with mobile network technology is used to realize data acquisition and transmission in motion scenes. In this paper, a fuzzy image recovery algorithm is designed and implemented to process fuzzy image data collected by equipment. In the experiment, the algorithm is trained and verified by using the image data in different motion scenes, and its recovery effect is analyzed. Experiments show that the proposed fuzzy image recovery algorithm can effectively improve the clarity and detail capture of images, and make the status monitoring of athletes more timely and reliable combined with the real-time data transmission of wireless sensor networks. Therefore, wearable optical imaging equipment based on wireless sensor network and fuzzy image recovery algorithm shows a good application prospect in sports image analysis, which can provide important support for athletes’ training and performance evaluation, and promote the intelligent process in the field of sports.</p>","PeriodicalId":501103,"journal":{"name":"Mobile Networks and Applications","volume":"6 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mobile Networks and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s11036-024-02405-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the rapid development of Internet of Things technology, wearable optical imaging devices can monitor the status and performance of athletes in real time, but the image quality is affected by environmental factors, often resulting in information loss. This study aims to improve the effectiveness of wearable optical imaging devices in sports image analysis by using wireless sensor networks and fuzzy image recovery algorithms, so as to achieve more accurate motion state monitoring. Wireless sensor network architecture combined with mobile network technology is used to realize data acquisition and transmission in motion scenes. In this paper, a fuzzy image recovery algorithm is designed and implemented to process fuzzy image data collected by equipment. In the experiment, the algorithm is trained and verified by using the image data in different motion scenes, and its recovery effect is analyzed. Experiments show that the proposed fuzzy image recovery algorithm can effectively improve the clarity and detail capture of images, and make the status monitoring of athletes more timely and reliable combined with the real-time data transmission of wireless sensor networks. Therefore, wearable optical imaging equipment based on wireless sensor network and fuzzy image recovery algorithm shows a good application prospect in sports image analysis, which can provide important support for athletes’ training and performance evaluation, and promote the intelligent process in the field of sports.