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Application of Asynchronous Multi-sensor in the Fusion of School Sports, Home Sports and Community Sports

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1147))

Abstract

Community sports, school sports and home sports run through human lifelong sports. Community sports have a wide audience and can participate in sports activities. School sports are an important part of lifelong sports. Family sports are important for the development of children’s physical exercise Impact. The application of multi-sensor data fusion technology in various fields, of which the current research is more focused on the problem of synchronous data fusion, that is, it is assumed that each sensor measures the target synchronously and transmits the data to the fusion center synchronously. But often encountered in practice It is an asynchronous fusion problem. Based on the above background. The research content of this paper is the application of asynchronous multi-sensors in the fusion of school sports, home sports and community sports. In this paper, the problem of asynchronous multi-rate measurement processing in multi-sensor detection environment is studied. Under the condition that the fusion center filtering speed is slow and the sensor sampling rate is fast, one fusion cycle needs to process multiple asynchronous measurement data. The pseudo measurement method can make full use of multiple time series and multiple quantities of measurement information in a fusion cycle, and combine the model’s pre-push information at the fusion time to build a time-synchronized pseudo measurement. Through these methods, the asynchronous fusion problem is transformed into a mature solution. Fusion problem of simultaneous measurement. Finally, the experimental simulation shows that CR = 0.0801 < 0.11, so the judgment matrix has acceptable consistency. And the noise correlation processing can improve the tracking accuracy, but because the increase is small and the matrix inversion operation is increased, it is necessary to make a proper trade-off between accuracy and calculation amount when applying this method.

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References

  1. Doucette, M.L., Bulzacchelli, M.T., Gillum, T.L., et al.: The Massachusetts school sports concussions law: a qualitative study of local implementation experiences. J. Law Med. Ethics 44(3), 503–513 (2016)

    Article  Google Scholar 

  2. Aslan, C.S.: Comparison of the physical education and sports school students’ multiple intelligence areas according to demographic features. Educ. Res. Rev. 11(19), 1823–1830 (2016)

    Article  Google Scholar 

  3. Mckenzie, T.L., Nader, P.R., Strikmiller, P.K., et al.: School physical education: effect of the child and adolescent trial for cardiovascular health. Prev. Med. 25(4), 423 (2016)

    Article  Google Scholar 

  4. Kerr, Z.Y., Roos, K.G., Djoko, A., et al.: Rankings of high school sports injury rates differ based on time loss assessments. Clin. J. Sport Med. 27(6), 548–551 (2016)

    Article  Google Scholar 

  5. Morin, P., Lebel, A., Robitaille, É., et al.: Socioeconomic factors influence physical activity and sport in quebec schools. J. Sch. Health 86(11), 841–851 (2016)

    Article  Google Scholar 

  6. Eyler, A.A., Piekarz-Porter, E., Serrano, N.H.: Pay to play? State laws related to high school sports participation fees. J. Public Health Manag. Pract. JPHMP 25(3), E27–E35 (2018)

    Article  Google Scholar 

  7. Barney, D., Pleban, F.T., Wilkinson, C., et al.: Identifying high school physical education physical activity patterns after high school. Phys. Educ. 72(2), 278–293 (2015)

    Google Scholar 

  8. Mckay, C., Block, M., Park, J.Y.: The impact of paralympic school day on student attitudes toward inclusion in physical education. Adap. Phys. Act. Q.: APAQ 32(4), 331–348 (2015)

    Google Scholar 

  9. Pu, W., Liu, Y.F., Yan, J., et al.: Optimal estimation of sensor biases for asynchronous multi-sensor registration. Math. Program. 170(1), 357–386 (2017)

    Article  Google Scholar 

  10. Yang, M., Liu, S.C., Delbruck, T.: A dynamic vision sensor with 1% temporal contrast sensitivity and in-pixel asynchronous delta modulator for event encoding. IEEE J. Solid-State Circuits 50(9), 2149–2160 (2015)

    Article  Google Scholar 

  11. Lin, H., Sun, S.: Distributed fusion estimation for multi-sensor asynchronous sampling systems with correlated noises. Int. J. Syst. Sci. 48(5), 952–960 (2016)

    Article  MathSciNet  Google Scholar 

  12. Lee, W., Youn, I.H., Song, T., et al.: Prime block design for asynchronous wake-up schedules in wireless sensor networks. IEEE Commun. Lett. 20(1437), 1440 (2016)

    Google Scholar 

  13. Zuo, J., Zhong, X.: Particle filter for nonlinear systems with multi-sensor asynchronous random delays. J. Syst. Eng. Electron. 28(6), 1064–1071 (2017)

    Article  MathSciNet  Google Scholar 

  14. Zou, Y., Wan, Q.: Asynchronous time-of-arrival-based source localization with sensor position uncertainties. IEEE Commun. Lett. 20(9), 1860–1863 (2016)

    Article  Google Scholar 

  15. Yang, X., Zhang, W.A., Chen, M.Z.Q., et al.: Hybrid sequential fusion estimation for asynchronous sensor network-based target tracking. IEEE Trans. Control Syst. Technol. 25(2), 669–676 (2017)

    Article  Google Scholar 

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Acknowledgement

This work was supported by General Events of Jiangxi Sports Bureau (No. 2019002).

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Correspondence to Fubin Wang .

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Wang, F., Huang, Q. (2020). Application of Asynchronous Multi-sensor in the Fusion of School Sports, Home Sports and Community Sports. In: Xu, Z., Parizi, R., Hammoudeh, M., Loyola-González, O. (eds) Cyber Security Intelligence and Analytics. CSIA 2020. Advances in Intelligent Systems and Computing, vol 1147. Springer, Cham. https://doi.org/10.1007/978-3-030-43309-3_6

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