通过光调制提高睡眠质量 基于物联网的方法 ESP32 与飞利浦 Hue 集成

Q2 Engineering
Ysl Ron Hepos, Kimuel Lagnason, Philipcris Encarnacion
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引用次数: 0

摘要

本研究旨在利用 ESP32 微控制器、飞利浦 Hue Bridge 和灯泡技术,开发基于定制物联网(IoT)的系统,从而彻底改变睡眠质量。主要目标是确定有利于改善睡眠的最佳照明条件,同时考虑色彩强度等因素,并与用户的昼夜节律保持一致。该系统可根据个性化配置文件动态控制光照强度和颜色,并与一天中的不同时间同步,从而提高睡眠质量。基于年龄的用户配置文件的整合完善了这些灯光配置文件,满足了不同年龄组的不同睡眠需求。真实世界的实验成功验证了该系统在不同年龄段的有效性,证明了它在量身定制的睡眠解决方案中的应用。这项研究为物联网驱动的睡眠干预做出了重大贡献,为行业内的个性化方法设定了新标准。在成功实施测试阶段的基础上,还提出了进一步完善和扩展该系统的建议,如探索更多环境因素以增强个性化、改进算法以改善实时调整,以及考虑用户反馈以持续优化系统。这项研究提出了一种开创性的睡眠改善解决方案,并为基于物联网的个性化干预措施的未来发展提供了路线图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced Sleep Quality Through Light Modulation IoT-Based Approach ESP32 with Philips Hue Integration
This research aims to revolutionize sleep enhancement by developing a customized Internet of Things (IoT)-based system utilizing the ESP32 microcontroller, Philips Hue Bridge, and Bulb technology. The primary objective is to identify optimal lighting conditions conducive to improved sleep, considering factors such as color intensity and aligning with users' circadian rhythms. The system dynamically controls light intensity and color based on personalized profiles, synchronized with distinct times of the day, enhancing sleep quality. The integration of user profiles based on age refined these light profiles, addressing diverse sleep needs across age groups. Real-world experiments successfully validated the system's effectiveness across various age categories, demonstrating its application for tailored sleep solutions. The study makes a significant contribution to IoT-driven sleep interventions, setting a new standard for personalized approaches in the industry. Based on the successful implementation of the testing phase, recommendations for further refinement and expansion of the system are provided, such as exploring additional environmental factors for enhanced personalization, refining algorithms for improved real-time adjustments and considering user feedback for continuous system optimization. The study presents a groundbreaking solution for sleep enhancement and provides a roadmap for future advancements in personalized IoT-based interventions.
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