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@article{179139,
        author = {Ashwini G A and Bhoomika A and Janasree J and Bala Abirami B},
        title = {Underwater Waste sorting and classification detection system using yolov8 and django},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {5821-5825},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179139},
        abstract = {The increasing complexity of waste management necessitates advanced technological solutions to enhance efficiency and sustainability. This paper introduces a real-time waste classification and sorting system that leverages YOLOv8, an advanced object detection model, to categorize waste with high precision. The system facilitates automated waste identification, streamlining sorting and recycling processes. By recognizing and classifying different waste types, including recyclables, organic matter, and general waste, YOLOv8 ensures accurate detection through deep learning methodologies. To enhance functionality and user interaction, the system is seamlessly integrated with Django, a robust web framework that provides a scalable and intuitive platform for data management and real-time processing. Through this integration, users receive instant feedback on proper waste disposal practices based on the system's classification results. The approach not only minimizes human sorting errors but also encourages environmentally responsible disposal habits, thereby improving overall waste management effectiveness. This solution is designed to support sustainable waste disposal practices, reduce landfill dependency, and enhance recycling rates in urban and industrial environments. Experimental evaluations demonstrate high classification accuracy, rapid processing speeds, and adaptability across diverse waste categories, making it a suitable tool for smart cities, waste collection centers, and industrial applications. By incorporating computer vision, deep learning, and web-based automation, this system lays the groundwork for an intelligent, data-driven waste management strategy that contributes to a more sustainable future.},
        keywords = {Waste sorting, Recycling classification, YOLOv8 object detection model, Django web framework, Realtime waste classification, Waste category identification, User-friendly interface.},
        month = {May},
        }