Ysl Ron Hepos, Kimuel Lagnason, Philipcris Encarnacion
{"title":"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","authors":"Ysl Ron Hepos, Kimuel Lagnason, Philipcris Encarnacion","doi":"10.30534/ijeter/2024/021262024","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":" 45","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced Sleep Quality Through Light Modulation IoT-Based Approach ESP32 with Philips Hue Integration\",\"authors\":\"Ysl Ron Hepos, Kimuel Lagnason, Philipcris Encarnacion\",\"doi\":\"10.30534/ijeter/2024/021262024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":13964,\"journal\":{\"name\":\"International Journal of Emerging Trends in Engineering Research\",\"volume\":\" 45\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Emerging Trends in Engineering Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30534/ijeter/2024/021262024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Emerging Trends in Engineering Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30534/ijeter/2024/021262024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
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.