Tackling food waste in nursing homes: A measurement method using smart bins

Food waste is a critical issue in the food service sector, including nursing homes. Effective monitoring of food waste is essential for its prevention and valorisation, though it presents challenges, especially for long-term tracking. This study introduces a novel smart bin-based measurement method for quantifying and characterising food waste in nursing homes. The method integrates an automation of data collection, structured data processing, and multi-level categorisation. A case study has been conducted in one nursing home in Borås, Sweden, to assess the feasibility of the method. The preliminary results were presented from multiple perspectives, including weekly waste across all meals and overall waste distribution by type and composition, highlighting the method's versatility. On average, lunch waste amounted to 78 g per portion, comprising 52 % plate waste and 48 % serving waste. For dinner, waste averaged 58 g per portion, with 68 % plate waste and 31 % serving waste. The largest contributors to waste were mixed dishes and potatoes. This study demonstrates the method's effectiveness in capturing food waste dynamics with high granularity and potential for scalable, long-term food waste monitoring in institutional settings, offering a foundation for AI-driven classification and data-driven interventions.