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@article{169009,
        author = {Pawan Makhare and Varad Chavan and Sankalp Shinde and Nilesh Yadav},
        title = {Cost-Efficient AI-Driven Waste Segregation System Utilizing Image Processing},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {418-420},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169009},
        abstract = {Efficient waste management is crucial to minimizing environmental impact and improving recycling rates. This paper presents a smart bin system designed to automate waste segregation through image processing and machine learning techniques. The system captures images of waste using a camera module, processes these images using OpenCV, and employs a TensorFlow-based classification model to categorize waste into plastic, metal, organic, paper, and unidentified categories. A processing unit like the ESP32 or Raspberry Pi is used to control the motorized bin system, which automatically directs waste into the appropriate container. The system is further enhanced with sensors that monitor bin levels and provide real-time feedback through LEDs. By automating the waste segregation process, this project aims to reduce human intervention and accelerate recycling efforts.},
        keywords = {},
        month = {November},
        }