Exploring The Relationship Between Sleep Quality And Micro-climate With The Internet Of Things

This study investigates the impact of environmental factors—light, dust level, sound, temperature, and humidity—on sleep stages (Awake, InBed, Core, Deep, and REM). The research aims to explore correlations, differences, and the predictive significance of these factors on sleep stages. Data were collected using an Apple Watch for sleep tracking and Seeed sensors for environmental measurements across two distinct settings: a dormitory in Singapore and a home in Vietnam. Statistical methods, including Spearman’s and Pearson’s correlation, the Kruskal-Wallis H Test, and post-hoc analyses, were employed to analyze relationships between variables. The findings reveal weak correlations between environmental factors and sleep stages, suggesting that while these factors influence sleep patterns, their effects are limited. Differences in environmental conditions across sleep stages were noted, but their magnitude remained minimal. Predictive accuracy for sleep stages using environmental factors was modest, indicating the potential need for nonlinear modeling techniques such as neural networks