Improving Students' Learning Effectiveness by an AIoT Human Centric Lighting System

This study aims to develop an AIoT human- centric lighting (HCL) system, encompassing its service platform and algorithms for analyzing and regulating circadian rhythms. The HCL system seamlessly integrates daylight-linked control into the IoT architecture, enabling remote control of luminaires, sen...

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Bibliographic Details
Published in2023 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI) pp. 180 - 181
Main Authors Yang, Ya-Ting, Chiang, Wei-Chun, Wang, Jeen-Shing
Format Conference Proceeding
LanguageEnglish
Published IEEE 08.07.2023
Subjects
Academic Achievement
Acceptance and Commitment Therapy
AIoT
Depression
Emotion recognition
Human Centric Lighting
Lighting
Lighting control
Medical treatment
Optimal control
Psychology
Sleeping Duration
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Summary:This study aims to develop an AIoT human- centric lighting (HCL) system, encompassing its service platform and algorithms for analyzing and regulating circadian rhythms. The HCL system seamlessly integrates daylight-linked control into the IoT architecture, enabling remote control of luminaires, sensor data collection in classrooms, and the establishment of a cloud-based data-driven model. By leveraging optimal control theory, the system ensures consistent target settings for classroom illumination. The objective of this study is to investigate the effectiveness and long-term impact of the proposed lighting strategy, combined with acceptance and commitment therapy (ACT), on students' sleep duration, depression levels, and learning effectiveness. Purposive sampling was conducted, involving four 10th-grade classes. The results of MANCOVA demonstrate that the posttests for sleep duration, depression, and academic achievement in the ACT class, the lighting strategy class (AIoT-based HCL system), and the combined lighting strategy with ACT class were significantly superior to those of the comparison class.
DOI:10.1109/IIAI-AAI59060.2023.00045