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基于学习情境的教室自优化智能照明系统的开发与实现。

Development and Implementation of a Self-Optimizable Smart Lighting System Based on Learning Context in Classroom.

机构信息

Department of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L3G1, Canada.

Suzhou Shuyan Information Technology Ltd., 18F, 58 Qing Long Gang Rd, Suzhou 215000, China.

出版信息

Int J Environ Res Public Health. 2020 Feb 13;17(4):1217. doi: 10.3390/ijerph17041217.

DOI:10.3390/ijerph17041217
PMID:32070046
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7068364/
Abstract

Illumination is one of the most important environmental factors in the classroom. Researchers have discovered that lighting settings have significant impact on students' performance. Although light-emitting diode (LED) lighting systems can precisely control brightness level and correlated color temperature (CCT), existing designs of LED lighting control systems for classrooms are focused on energy-saving but lack context-based illumination control ability. In this study, a smart lighting system with continuous evolution capability was developed. It can adjust brightness, CCT, and illuminance distribution dynamically according to specific learning context. This system allows not only manual control, but also automatic switching of scenes by integrating with school schedules. Based on existing knowledge about lighting preference, 10 lighting modes confined in the comfortable zone of Kruithof curve were proposed for various classroom scenarios. Moreover, a classroom environmental data-processing framework for collecting and analyzing learning context, illumination settings, environmental data, and students' performance data was introduced. This framework can help researchers explore the correlation between student performance and environmental parameters.

摘要

照明是教室环境中最重要的因素之一。研究人员发现，照明设置对学生的表现有重大影响。虽然发光二极管（LED）照明系统可以精确控制亮度水平和相关色温（CCT），但现有的教室 LED 照明控制系统设计侧重于节能，但缺乏基于上下文的照明控制能力。在本研究中，开发了一种具有连续进化能力的智能照明系统。它可以根据特定的学习环境动态调整亮度、CCT 和照度分布。该系统不仅允许手动控制，还可以通过与学校时间表集成实现场景的自动切换。基于现有的照明偏好知识，针对各种教室场景提出了 10 种限制在克鲁伊特夫曲线舒适区的照明模式。此外，还介绍了一个教室环境数据处理框架，用于收集和分析学习环境、照明设置、环境数据和学生表现数据。该框架可以帮助研究人员探索学生表现和环境参数之间的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/15949989ae75/ijerph-17-01217-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/824760489285/ijerph-17-01217-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/4f261a8ee66a/ijerph-17-01217-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/58bec9a26f70/ijerph-17-01217-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/86b163116530/ijerph-17-01217-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/5d72c17a09c9/ijerph-17-01217-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/9253bf7a813c/ijerph-17-01217-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/f24f3f2c4ece/ijerph-17-01217-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/1c47bee2d601/ijerph-17-01217-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/ed6f440799c3/ijerph-17-01217-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/1341af667584/ijerph-17-01217-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/d4d3cce3aa6c/ijerph-17-01217-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/8d64e32d97b1/ijerph-17-01217-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/1a6a90edea42/ijerph-17-01217-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/c3707e87aee4/ijerph-17-01217-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/1354d501cce3/ijerph-17-01217-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/ac427a6729fc/ijerph-17-01217-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/d795530a7ce4/ijerph-17-01217-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/bf91a29b1e05/ijerph-17-01217-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/cb093696eeb5/ijerph-17-01217-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/9b62d76d9157/ijerph-17-01217-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/15949989ae75/ijerph-17-01217-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/824760489285/ijerph-17-01217-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/4f261a8ee66a/ijerph-17-01217-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/58bec9a26f70/ijerph-17-01217-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/86b163116530/ijerph-17-01217-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/5d72c17a09c9/ijerph-17-01217-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/9253bf7a813c/ijerph-17-01217-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/f24f3f2c4ece/ijerph-17-01217-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/1c47bee2d601/ijerph-17-01217-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/ed6f440799c3/ijerph-17-01217-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/1341af667584/ijerph-17-01217-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/d4d3cce3aa6c/ijerph-17-01217-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/8d64e32d97b1/ijerph-17-01217-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/1a6a90edea42/ijerph-17-01217-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/c3707e87aee4/ijerph-17-01217-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/1354d501cce3/ijerph-17-01217-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/ac427a6729fc/ijerph-17-01217-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/d795530a7ce4/ijerph-17-01217-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/bf91a29b1e05/ijerph-17-01217-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/cb093696eeb5/ijerph-17-01217-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/9b62d76d9157/ijerph-17-01217-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6fa/7068364/15949989ae75/ijerph-17-01217-g021.jpg

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