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Littering Management Using AI
Subject area: Science,Engineering and Technology · Area of research: Machine Learning
DOI: https://doi.org/10.64388/IREV9I6-1712601
Abstract
Littering is one of the major environmental challenges faced by modern societies. It leads to land, water, and air pollution and affects both human health and wildlife. Traditional waste monitoring systems rely heavily on manual inspection which is time-consuming, costly, and inefficient. With the rapid development of Artificial Intelligence (AI), automated litter detection and waste management systems have become possible. This paper presents a comprehensive study on AI-based littering management systems using deep learning and computer vision techniques. The proposed system uses surveillance cameras, image processing, and deep neural networks to detect, classify, and track litter in real time. The system also generates automated alerts for timely waste collection, thereby improving cleanliness and supporting smart city initiatives.
Keywords
Artificial Intelligence, Litter Detection, Waste Management, Deep Learning, Computer Vision, Smart City, IoT
How to cite this paper
@article{1712601,
author = {Deekshith B N, H V Revanth Gowda, Karthik Kumar H R, Kiran Hemappa Madiwalar, Abdul Rahaman},
title = {Littering Management Using AI},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {6},
pages = {153-157},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712601.pdf},
abstract = {Littering is one of the major environmental challenges faced by modern societies. It leads to land, water, and air pollution and affects both human health and wildlife. Traditional waste monitoring systems rely heavily on manual inspection which is time-consuming, costly, and inefficient. With the rapid development of Artificial Intelligence (AI), automated litter detection and waste management systems have become possible. This paper presents a comprehensive study on AI-based littering management systems using deep learning and computer vision techniques. The proposed system uses surveillance cameras, image processing, and deep neural networks to detect, classify, and track litter in real time. The system also generates automated alerts for timely waste collection, thereby improving cleanliness and supporting smart city initiatives.},
keywords = {Artificial Intelligence, Litter Detection, Waste Management, Deep Learning, Computer Vision, Smart City, IoT},
month = {December},
doi = {https://doi.org/10.64388/IREV9I6-1712601}
}