Sleep plays a crucial role in human health and well-being and is an evolving field in medical science. Access to reliable sleep quality data provides valuable insight into an individual's physical and mental fatigue, which can be used to make informed decisions in high-risk situations such as driving or operating heavy machinery. However, traditional sleep monitoring methods rely on expensive and intrusive medical equipment, limiting their accessibility for long-term and daily use. This thesis aims to develop a functional mobile solution that automates the collection of biometric sleep data using commercially available Garmin sports watches. The application also integrates an algorithm to analyze sleep data, determining the duration and quality of sleep.