International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Smart E-Waste Bin Using AI and IoT for Automated Waste Segregation

Author(s) Ms. Krishna Chandranil Karkhanis, Mr. Shriram Dattatray Jadhav, Prof. Neelam Jain
Country India
Abstract The increasing number of electronic devices has created an ever-growing amount of electronic waste (e-waste) and caused serious problems for both the environment and human health. Traditional waste management systems are inefficient because they use manual sorting methods which are difficult and prone to mistakes. A Smart E-Waste Bin is proposed which uses Artificial Intelligence (AI), Internet of Things (IoT), and computer vision for automating the detection of e-waste and sorting it.
The bins utilize a Convolutional Neural Network (CNN) model to classify waste into three categories (Electronic, Plastic, and Metal), and they incorporate an ultrasonic sensor for detecting when e-waste is placed in the bin as well as a camera to provide images for the classification of e-waste. After identifying the classification of waste, the microcontroller activates the servo motors to sort the waste into the appropriate compartment. In addition, the bins are connected to a cloud server for real-time monitoring and data analysis purposes. The proposed bin improves accuracy and reduces the amount of human work needed to efficiently manage e-waste; therefore, this solution is also well-suited for use in smart cities.
Keywords Artificial Intelligence (AI), Internet of Things (IoT), E-Waste Management, Smart Waste Bin, Computer Vision, Convolutional Neural Network (CNN), Automated Waste Segregation, Deep Learning, Embedded Systems, Cloud Monitoring.
Field Engineering
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-04-30
DOI https://doi.org/10.36948/ijfmr.2026.v08i02.76620
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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