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Online classroom teacher–student interaction system based on compressed sensing data collection and sensors

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Abstract

The current teaching mode mostly uses multimedia for teaching, but in the process of teaching, we have encountered some problems about information preservation and data query. Nowadays, the development of education is becoming more and more rapid, which means that traditional education methods can no longer adapt to the new development situation. For this reason, we analyzed the preparation and teaching methods of several higher teachers, and summarized them. Developed a practical and real-time online learning system that interacts with preparations and lectures. This paper summarizes the research status of wireless sensor network energy consumption at home and abroad. In addition, this paper analyzes the hardware structure and design of sensor nodes and the main algorithms and protocols required at each level on the premise of studying the sensor network architecture. In this article, we analyzed the hardware and protocol stack, and found the main reason for the energy consumption of sensor nodes, and also constructed the mathematical model required for wireless transmission energy consumption. Starting from the original compressed sensing method, this paper mainly studies the data collection method and data reconstruction method in wireless sensor networks. Finally, with the support of compressed sensing technology, we use receivers, transponders, etc. as part of the hardware structure, and at the same time, through the design of interactive teaching software, namely compressed sensing gateways, data access services, etc., we have established an interactive classroom teaching The framework of the system, through the design of the teaching system framework, teachers can answer questions, attendance, evaluation and other activities during online teaching, which greatly improves the development of classroom interactive teaching.

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References

  1. Saleh, M. A., Hashim, H., & Tahir, N. M. (2015). A low computational method of secure video streaming in mobile system. In 2014 IEEE symposium on computer applications & industrial electronics (ISCAIE) (pp. 193–197). IEEE.

  2. Unterweger, A., Ryckegem, K. V., Engel, D., & Uhl, A. (2015). Building a post-compression region-of-interest encryption framework for existing video surveillance systems. Multimedia Systems, 22(5), 1–23.

    Google Scholar 

  3. Khlif, N., Masmoudi, A., Kammoun, F., & Masmoudi, N. (2018). Secure chaotic dual encryption scheme for H.264/AVC video conferencing protection. IET Image Processing, 12(1), 42–52.

    Article  Google Scholar 

  4. Hamidouche, W., Farajallah, M., Sidaty, N., Assad, S. E., & Deforges, O. (2017). Real-time selective video encryption based on the chaos system in scalable HEVC extension. Signal Processing: Image Communication, 58, 73–86.

    Google Scholar 

  5. Chang, Y. T., & Lin, Y. C. (2016). Dynamic reconfigurable encryption and decryption with chaos/M-sequence mapping algorithm for secure H.264/AVC video streaming over OCDMA passive optical network. Multimedia Tools and Applications, 75(16), 9837–9859.

    Article  Google Scholar 

  6. Zhang, X., Yu, S., Chen, P., Lü, J., He, J., & Lin, Z. (2017). Design and ARM-embedded implementation of a chaotic secure communication scheme based on H.264 selective encryption. Nonlinear Dynamics, 89(8), 1–17.

    Article  Google Scholar 

  7. Saini, N., & Sinha, A. (2015). Video encryption using chaotic masks in joint transform correlator. Journal of Optics, 17(3), 73–93.

    Article  Google Scholar 

  8. Li, C., Xie, T., Liu, Q., & Cheng, G. (2014). Cryptanalyzing image encryption using chaotic logistic map. Nonlinear Dynamics, 78(2), 1545–1551.

    Article  Google Scholar 

  9. Zhou, Y., Hua, Z., Pun, C. M., & Philip Chen, C. L. (2015). Cascade chaotic system with applications. IEEE Transactions on Cybernetics, 45(9), 2001–2012.

    Article  Google Scholar 

  10. Tong, F. Z., Li, S. L., Ge, R. J., Yuan, M., & Ma, Y. (2016). A novel 1D hybrid chaotic map-based image compression and encryption using compressed sensing and Fibonacci-Lucas transform. Mathematical Problems in Engineering, 2016(3), 1–15.

    Article  MathSciNet  MATH  Google Scholar 

  11. Özkaynak, F. (2015). A novel method to improve the performance of chaos based evolutionary algorithms. Optik, 126(24), 5434–5438.

    Article  Google Scholar 

  12. Murillo-Escobar, M. A., Cruz-Hernández, C., Cardoza-Avendaño, L., & Méndez-Ramírez, R. (2017). A novel pseudorandom number generator based on pseudo randomly enhanced logistic map. Nonlinear Dynamics, 87(1), 407–425.

    Article  MathSciNet  Google Scholar 

  13. Liu, Y., Luo, Y., Song, S., Cao, L., Liu, J., & Harkin, J. (2017). Counteracting dynamical degradation of digital chaotic Chebyshev map via perturbation. International Journal of Bifurcation and Chaos, 27(3), 1750033.

    Article  MathSciNet  MATH  Google Scholar 

  14. Hua, Z., & Zhou, Y. (2017). Dynamic parameter-control chaotic system. IEEE Transactions on Cybernetics, 46(12), 3330–3341.

    Article  Google Scholar 

  15. Xu, H., Tong, X., & Meng, X. (2016). An efficient chaos pseudo-random number generator applied to video encryption. Optik International Journal Light Electron Optic, 127(20), 9305–9319.

    Article  Google Scholar 

  16. Sallam, A. I., Faragallah, O. S., & El-Rabie, E. S. M. (2018). HEVC selective encryption using RC6 block Cipher technique. IEEE Transactions on Multimedia, 20(7), 1636–1644.

    Article  Google Scholar 

  17. Ding, X., Deng, Y., Yang, G., Song, Y., He, D., & Sun, X. (2017). Design of new scan orders for perceptual encryption of H.264/AVC videos. IET Information Security, 11(2), 55–65.

    Article  Google Scholar 

  18. Ma, T., Ma, M., & Hu, F. (2017). Scalable protection scheme for the H.264/SVC video streaming. In International conference on wireless communications and signal processing (pp. 1–6).

  19. Boyadjis, B., Bergeron, C., Pesquet-Popescu, B., & Dufaux, F. (2017). Extended selective encryption of H.264/AVC (CABAC) and HEVC-encoded video streams. IEEE Transactions on Circuits and Systems for Video Technology, 27(4), 892–906.

    Article  Google Scholar 

  20. Zhou, Y., Bao, L., & Chen, C. L. P. (2014). A new 1D chaotic system for image encryption. Signal Processing, 97(7), 172–182.

    Article  Google Scholar 

  21. Zang, H. Y., & Chai, H. Y. (2016). Homogenization and entropy analysis of a quadratic polynomial chaotic system. Acta Physica Sinica, 65(3), 030504-1-030504–7.

    Google Scholar 

  22. Liu, S., Rho, S., Jifara, W., Jiang, F., & Liu, C. (2018). A hybrid framework of data hiding and encryption in H.264/SVC. Discrete Applied Mathematics, 241(31), 48–57.

    Article  MathSciNet  MATH  Google Scholar 

  23. Peng, F., Gong, X. Q., Long, M., & Sun, X. M. (2016). A selective encryption scheme for protecting H.264/AVC video in multimedia social network. Multimedia Tools and Applications, 76(3), 1–19.

    Google Scholar 

  24. Li, J., Wang, C., Chen, X., Tang, Z., Hui, G., & Chang, C.-C. (2018). A selective encryption scheme of CABAC based on video context in high efficiency video coding. Multimedia Tools and Applications, 77(10), 12837–12851.

    Article  Google Scholar 

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Acknowledgements

Teaching Reform Research Project of Ordinary Universities in Hunan Province "Research on Improving the Teaching Quality of Teacher–student Interaction in Teaching-oriented Universities" (Xiangjiao Tong [2019] No. 291)

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Correspondence to Weimei Zhang.

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Zhang, W., He, L. Online classroom teacher–student interaction system based on compressed sensing data collection and sensors. Wireless Netw (2021). https://doi.org/10.1007/s11276-021-02695-y

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