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@article{172435,
        author = {Nethravathi DN and Pooja N and Darshan BR and Yashvanth KB and Ms Namratha D},
        title = {Monitoring and segregation of E-waste and Non e-waste using CNN},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {3342-3348},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172435},
        abstract = {The increasing volume of waste, including electronic (e-waste) and non-electronic materials, highlights the urgent need for efficient waste management solutions. This paper proposes a smart system for Monitoring and segregation of e-waste and non-e-waste using a Convolutional Neural Network (CNN). The system employs a Raspberry Pi Zero 2W with a camera module to capture waste images and classify them into e-waste or non-e-waste categories in real-time. The classified data is integrated with a mobile application, enabling real-time monitoring and efficient coordination for collection and recycling. The smart bin also features ultrasonic sensors for waste level detection and motorized segregation to ensure accurate disposal. By leveraging edge computing, the system offers a cost-effective, fast, and sustainable solution for managing waste while promoting responsible recycling practices.},
        keywords = {},
        month = {January},
        }