AI-Enhanced Application for Incentivizing Waste Recycling: A Step Towards Sustainable Environment

Waste recycling is a crucial component of environmental sustainability. However, its adoption remains limited, especially in developing countries where weak recycling infrastructures and low public engagement present significant challenges. While advanced regions have leveraged artificial intelligence (AI) and object recognition technologies to optimize waste management, these innovations have yet to be fully integrated into resource-constrained settings. Addressing this gap, this study proposes an AI-enhanced mobile application designed to encourage and facilitate recycling by combining education, gamification, and reward-based incentives. The proposed platform educates users on proper waste segregation and recycling techniques while employing an incentive-driven approach to promote sustained behavioral change. This study compares two models, YOLOv8 and YOLO11, for waste classification and finds that YOLO11 outperforms YOLOv8, achieving mAP50 scores of 0.843 for glass, 0.774 for metal, and 0.673 for biodegradable materials. These results show that AI-enhanced, gamified systems can reinforce recycling habits, increase public engagement, and support sustainability. As such, this study offers a scalable framework for adopting AI in waste management, particularly in regions lacking formal recycling infrastructures.