General
Designed a data-driven digital twin system for improving sleep comfort in a smart-home context by connecting bedroom conditions, sleep-monitoring data, daily routines, and user preferences. The project explored how a digital representation of the bedroom could identify patterns affecting sleep and generate adaptive recommendations for a more personalized sleep environment.
Contribution to PI&V
- The digital twin is not only something to design, but also a data-driven way of thinking about system structure.
- The course strengthened my interest in using data-driven systems thinking to support everyday well-being.
Involved Expertise Areas
- MD&C: sleep-data interpretation, digital twin role definition, data visualization, pattern-based personalization
- T&R: smart-home digital twin system design, data-informed interface prototyping