Abstract
With the increase in the amount of large data on the Internet, the content of the data has become complicated, and it is difficult for traditional methods to efficiently process the data. This article introduces the basic technologies of big data processing in mobile networks, such as multi-source data collection in mobile networks, large-scale heterogeneous data processing, real-time data mining, and powerful data analysis and presentation technologies. Visual target tracking technology is a research content that combines computer graphics research, image recognition, matrix theory, probability theory and other interdisciplinary content. This article analyzes the characteristics of the sports industry in the digital age and discusses the challenges of digital applications that lead China's digital development. The results show that the characteristics of China's digital age are the improvement of supply, the increase of production efficiency, the growth of the audience, the enrichment of content and the booming development of the consumer market. The Internet sports business ecosystem has become the main way of competition in the sports industry. The Internet will reshape the sports industry, break the monopoly of traditional commerce and media on sports intellectual property rights, open up sports-related industries, and enable users to receive a wide range of services on the Internet. In this article, Internet big data are used to visually track targets and research the sports industry, which is essential for digital development.
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References
Chong J, Liu P, Zhou G, Xia J (2020) Using MicrobiomeAnalyst for comprehensive statistical, functional, and meta-analysis of microbiome data. Nat Protoc 15(3):799–821
Gao P, Yue S, Chen H (2021) Carbon emission efficiency of China’s industry sectors: from the perspective of embodied carbon emissions. J Clean Prod 283:124655
Huda M, Maseleno A, Atmotiyoso P et al (2018) Big data emerging technology: insights into innovative environment for online learning resources. Int J Emerg Technol Learn (iJET) 13(1):23–36
Kerpedjiev P, Abdennur N, Lekschas F et al (2018) HiGlass: web-based visual exploration and analysis of genome interaction maps. Genome Biol 19(1):1–12
Koumoulos EP, Trompeta AF, Santos RM et al (2019) Research and development in carbon fibers and advanced high-performance composites supply chain in Europe: a roadmap for challenges and the industrial uptake. J Compos Sci 3(3):86
Litvinenko VS (2020) Digital economy as a factor in the technological development of the mineral sector. Nat Resour Res 29(3):1521–1541
Luo J, Han Y, Fan L (2018) Underwater acoustic target tracking: a review. Sensors 18(1):112
Lv X, Lian X, Tan L, Song Y, Wang C (2021) HPMC: a multi-target tracking algorithm for the IoT. Intell Autom Soft Comput 28(2):513–526
Nikou S, Aavakare M (2021) An assessment of the interplay between literacy and digital technology in higher education. Educ Inf Technol 26(4):3893–3915
Oussous A, Benjelloun FZ, Lahcen AA, Belfkih S (2018) Big Data technologies: a survey. J King Saud Univ-Comput Inf Sci 30(4):431–448
Ribeiro EG, de Queiroz MR, Grassi V Jr (2021) Real-time deep learning approach to visual servo control and grasp detection for autonomous robotic manipulation. Robot Auton Syst 139:103757
Shalabodina V (2021) The concept of the textbook modernization in the era of information technologies: physical education and challenges of modernity. ARPHA Proc 4:795–811
Sokolowski SL (2019) Sports industry meets academia: The pedagogical development of an MS degree program in sports product design. Technol Innov 20(3):165–177
Wan J, Yin B, Li D et al (2018) An ontology-based resource reconfiguration method for manufacturing cyber-physical systems. IEEE/ASME Trans Mechatron 23(6):2537–2546
Xia Y, Fan Y (2020) Security analysis of sports injury medical system based on internet of health things technology. IEEE Access 8:211358–211370
Zhong H, Miao Z, Wang Y et al (2019) A practical visual servo control for aerial manipulation using a spherical projection model. IEEE Trans Ind Electron 67(12):10564–10574
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Sheng, C., Liya, G., Rui, X. et al. Digital development of sports industry based on mobile networks and visual target tracking. Soft Comput (2023). https://doi.org/10.1007/s00500-023-08940-0
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DOI: https://doi.org/10.1007/s00500-023-08940-0