Ecowatch - Machine Learning Based Litter Detection

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Govind Kela; Aniket Kesarwani; Advait Khaire; Reena Sonkusare

Ecowatch - Machine Learning Based Litter Detection

Authors: Govind Kela, Aniket Kesarwani, Advait Khaire, Reena Sonkusare

Unique Paper ID: 174450
Volume: 11
Issue: 10
PageNo: 4594-4597

Keywords: No Keywords Found

Abstract:
Urban environments face significant challenges due to litter accumulation, adversely affecting public health, wildlife, and overall environmental sustainability. Existing manual detection and cleanup methods are inefficient, prompting the need for automated solutions. This paper presents EcoWatch, a real-time litter detection system leveraging advanced machine learning models—YOLOv8 and Faster R-CNN—to identify and classify litter from moving vehicles. By utilizing the TACO dataset, EcoWatch demonstrates its ability to accurately detect various litter types, including plastic bottles, aluminum cans, glass bottles, and food wrappers, under diverse environmental conditions.

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ISSN: 2349-6002
Volume: 11
Issue: 10
PageNo: 4594-4597

Ecowatch - Machine Learning Based Litter Detection

Available:https://ijirt.org/article?manuscript=174450

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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