IoT-Enabled Sustainable Food Waste Reduction Strategies in Dining Establishments

Food waste in dining establishments remains a critical issue, leading to significant economic losses, environmental degradation, and operational inefficiencies. This study addresses the problem by investigating sustainable food waste reduction strategies and evaluating their effectiveness through IoT-enabled solutions. Primary data was collected from restaurant owners, managers, and staff using structured surveys and direct observations, complemented by real-time data from IoT-based weight sensors, smart inventory systems, and analytics platforms. Statistical methods such as descriptive analysis, chi-square tests, t-tests, ANOVA, correlation, and regression were applied to identify key factors influencing food waste reduction. The findings reveal that IoT-enabled interventions significantly decreased food waste volume, optimized portion sizes, improved menu planning, and supported surplus food redistribution. Additionally, non-technological strategies such as staff training, portion customization, and customer engagement were identified as essential measures. The study demonstrates that combining IoT technology with behavioral strategies enhances operational efficiency, reduces costs, and promotes environmental sustainability. This research offers a replicable framework for the hospitality sector and contributes to achieving the United Nations Sustainable Development Goal 12: Responsible Consumption and Production.