Research and design of intelligent light control system based on IPV6

Hongshu Yan; Changwei Zhao; Xinhao Zhou

doi:10.1117/12.2625094

6 December 2021 Research and design of intelligent light control system based on IPV6

Hongshu Yan, Changwei Zhao, Xinhao Zhou

Proceedings Volume 12085, International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021); 1208507 (2021) https://doi.org/10.1117/12.2625094
Event: 2021 International Conference on Green Communication, Network, and Internet of Things, 2021, Kunming, China

Abstract

Energy is an important component of a country's economic development, and power resources are also an indispensable energy in people's production and life. There is also a large amount of energy waste caused by low lighting management efficiency in universities. This paper has designed a new intelligent light control system based on IPV6 network, using the network camera installed in the classroom to transfer the classroom image to the server through the IPV6 network. Through image processing, the data in the classroom is obtained and sent to the light control module to control the switch of the classroom light, supplemented by the manual control module, clock control module and photosensitive module, etc., and finally realize the intelligent management of the classroom lighting. Through the test of the intelligent light control system based on IPv6 network, the system has high sensitivity to moving images. For classrooms with different lighting conditions, large changes in pedestrian density and large randomness of use time, the control of the system can achieve accurate regulation. The whole system has low cost and high reliability. It is very suitable for classroom lighting control in teaching units and has good application value.

Citation Download Citation

Hongshu Yan, Changwei Zhao, and Xinhao Zhou "Research and design of intelligent light control system based on IPV6", Proc. SPIE 12085, International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021), 1208507 (6 December 2021); https://doi.org/10.1117/12.2625094

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