Title: Implementation of smart dustbin – a CNN-based intelligent waste management

Authors: M. Yuvashri; S.K. Varsha; M. Vijayalakshmi

Addresses: Thiagarajar College of Engineering, Madurai, Tamil Nadu, India ' Thiagarajar College of Engineering, Madurai, Tamil Nadu, India ' Thiagarajar College of Engineering, Madurai, Tamil Nadu, India

Abstract: Waste generation across the globe is adversely increasing and the classification of waste has become tedious affecting the process of recycling and increasing the environmental risks so we devised a simple way to classify waste as biodegradable and non-biodegradable economically using an Arduino-embedded smart dustbin. Our automatic waste sensing smart dustbin is introduced as a revolutionary marvel of technology! Meticulously designed to revolutionise waste management, this innovative smart dustbin incorporates cutting-edge programming. With this advanced technology, our dustbin ensures that its lid is exclusively opened by biodegradable waste, delivering a seamless and eco-friendly dumping experience for our users. The classification is done using our CNN-based residual network model and the accuracy of our metrics turned out to be 95.6% for a random sample batch of 32 images.

Keywords: waste management; smart dustbin; garbage classification; machine learning; object recognition; image processing; CNN model; computer vision; internet of things; IoT; ResNet model.

DOI: 10.1504/IJEWM.2025.146555

International Journal of Environment and Waste Management, 2025 Vol.37 No.2, pp.149 - 160

Received: 17 Oct 2022
Accepted: 22 May 2023
Published online: 04 Jun 2025 *

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