AI-Powered Food Waste Reduction and Smart Recipe Recommendation System

Food waste has emerged as a serious global challenge, particularly at the household level, where food is often discarded due to poor planning, lack of awareness about stored items, and missed expiry dates. Prior research has investigated the use of artificial intelligence and data-driven approaches to improve food management, including systems for food recognition, inventory tracking, and intelligent decision support. Studies on AI-based food waste management highlight the potential of automation and predictive techniques to reduce unnecessary disposal of edible food [1], [2]. In parallel, computer vision-based food and ingredient recognition systems have been widely studied to support smart kitchen applications. These approaches demonstrate that deep learning models can accurately identify food items from images, enabling automated inventory monitoring and reduced manual effort [3], [4]. Additionally, recipe recommendation systems have been explored to assist users in meal planning by suggesting dishes based on available ingredients or user preferences [5], [6]. However, existing recommendation systems primarily focus on personalization and convenience rather than food waste reduction.