In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice. 1. Zhang J R., Luo Y Q. Design and Research on University Classroom Energy Saving System Based on Microcomputer Control. Modern Computer, 2018, V28, #10, pp.100–108.
2. Shi­Yun W U., Luo J., Wang Y Y. Design of lighting energy­saving intelligent control system for college classroom based on microcontrollers. Electronic Design Engineering, 2016, V8, #2, pp. 64–70.
3. Mao J. The design of classroom energy saving control system based on single chip microcomputer. Electronic Design Engineering, 2016, V12, #2, pp.89–112.
4. Chao L I., Yang S L., Chen Y Q. Design of Classroom Intelligent Energy Saving System Based on WSNs and Power Line Communications. Measurement & Control Technology, 2017, V10, #4, pp.87–91.
5. Cai Xia., L U. Smart Home Based on Embedded Linux Lighting Energy Saving Research and Implementation of Control System Design. Microelectronics & Computer, 2016, V1, #5, pp.5–9.
6. Liao N. Development of the energy­saving lights control system design based on city­based wireless network. Machine Design & Manufacturing Engineering, 2016, V60, #1, pp.81–94.
7. Cui X., Yang D., Liu C. Research on the Support System of Green Entrepreneurship Based on the Case Study about Photovoltaic, Energy Saving Lighting, and New Energy Vehicles. Science & Technology Management Research, 2016, V2, #2, pp.47–53.
8. Zhang, WP., Yang, JZ., Fang, YL., Chen, HY., Mao, YH., Kumar, M. Analytical fuzzy approach to biological data analysis, Saudi journal of biological sciences, 2017, V2, #3, pp.563–573.
9. Aderibigbe, A., Ogunjuyigbe, A., Ayodele, R., Samuel, I. The performance of a 3­Phase Induction Machine under Unbalance Voltage Regime. Journal of Engineering Science and Technology Review, 2017, V10, #5, pp.136–143.

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• machine vision technology
• classroom lighting
• energy saving
• a control system
• conventional lighting control (lc)