ABSTRACT Monitoring and measurement are crucial activities in managing and reducing the impact of food waste. In Europe, the average food waste per person was estimated at 131 kg, with approximately 10% originating from restaurants and foodservice. Unfortunately, there is a lack of detailed information regarding food waste in hospital settings. Despite this, effective hospital food management plays a significant role in the environmental, social, and economic well-being of patients, and is closely linked to their nutrition and recovery prospects. This research examines key studies on hospital food waste management, focusing on practical implications and identifying strategies for improving sustainability in hospital foodservice through artificial intelligence technologies. It explores emerging trends, opportunities, and challenges in measuring and monitoring food waste while considering patient satisfaction and nutrition as critical factors for sustainable healthcare systems, through a semi-integrative literature review. Precisely, the amount of food waste per patient per day varies depending on the meal, with breakfast waste at about 0.08 kg, lunch waste ranging from 0.15 to 0.47 kg, and dinner waste between 0.11 and 0.48 kg, with the highest values recorded for lunch. Furthermore, considering the imperative to improve data precision, this study introduces current solutions that integrate artificial intelligence, 3D scanners, and digital scales to classify food categories, measure waste quantities, and assess the corresponding economic and environmental impacts. This research is intended for both academic and industry professionals in the foodservice sector, providing valuable insights into developing environmentally friendly strategies and achieving sustainability goals.
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