文献类型：期刊文献

英文题名：Exploring the role of sports APP in (campus fitness) intelligent solutions using data fusion algorithm and internet of things

作者：Zhu, Chao[1]

通讯作者：Zhu, C[1]

机构：[1]Beijing Union Univ, Dept Phys Educ, Beijing 100101, Peoples R China

第一机构：北京联合大学体育部、体委

通讯机构：[1]corresponding author), Beijing Union Univ, Dept Phys Educ, Beijing 100101, Peoples R China.|[1141790]北京联合大学体育部、体委;[11417]北京联合大学;

年份：2022

卷号：13

期号：1

起止页码：40-48

外文期刊名：INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING

收录：EI(收录号：20221311862155);Scopus(收录号：2-s2.0-85127030266);WOS:【ESCI(收录号:WOS:000767855200005)】；

基金：This work was supported by the Academic Research Projects of Beijing Union University (No. SK60202102).

语种：英文

外文关键词：IoT; internet of things; multi-sensors; data fusion; weighted least-squares method; intelligent solutions

摘要：The purposes are to study how the multi-sensor Internet of Things (IoT) data fusion algorithm calculates in data fusion systems and improves the systems' fusion efficiency. An improved Weighted Least-Squares (WLS) algorithm is proposed for IoT data fusion, and how it processes massive data in a multi-sensor system is studied. Accordingly, a multi-sensor system for sports fitness is designed based on a data fusion algorithm. First, the purposes and demand for sports Application (APP) are analysed, to understand the problems and necessary improvements of such APP. Then, the implementation of the IoT and the classification of the data fusion algorithm of the IoT are explored. The WLS method is selected through comparison, and its implementation process and the data processing process are analysed and explained. Finally, the sports fitness system based on the IoT data fusion algorithm is designed and analysed. The results show that the wireless communication of a multi-sensor data fusion system is feasible and reliable. The variances calculated through the WLS method and the Arithmetic Mean (AM) method in data fusion are compared. The former value is about one-thousandth of the latter value, indicating that the data fusion based on WLS is advantageous over the traditional data fusion.