YOU ONLY LIVE ONCE V7 SALVAGING AND GARBAGE CATALOGUING CENTERED ASSISTANT

The ever-growing global population has heightened resource consumption and waste generation, emphasizing the urgent need for effective waste management to safeguard the environment. Unfortunately, the recycling industry grapples with persistent challenges, primarily in the realm of accurate trash classification, a critical factor for successful recycling. Manual sorting, often prone to errors due to subjective human judgment, hampers the recycling process, contributing to inefficiencies. Furthermore, the inherent risks associated with direct contact during the sorting of hazardous materials pose serious health concerns for the workers involved. In response to these challenges, we propose a revolutionary solution: the Trash Classification and Recycling Assistant utilizing YOLO variants V5-V7. This system, rooted in image classification techniques, seeks to elevate the precision of trash sorting. Notably, YOLO variant V7 emerges as the frontrunner, showcasing remarkable accuracy improvements. By harnessing the capabilities of advanced technology, this innovative approach not only streamlines waste sorting processes but also mitigates health risks linked to manual handling of toxic materials. The integration of YOLO variants V5-V7 represents a pivotal step towards ushering in a new era of efficiency and accuracy in recycling practices, thus significantly contributing to the overarching goal of environmental sustainability.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-15
DOI
https://doi.org/10.5281/zenodo.15781236
Primary Topic
Plant chemical constituents analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

YOU ONLY LIVE ONCE V7 SALVAGING AND GARBAGE CATALOGUING CENTERED ASSISTANT

Zenodo (CERN European Organization for Nuclear Research)
Plant chemical constituents analysis
article

YOU ONLY LIVE ONCE V7 SALVAGING AND GARBAGE CATALOGUING CENTERED ASSISTANT

article en

Abstract

The ever-growing global population has heightened resource consumption and waste generation, emphasizing the urgent need for effective waste management to safeguard the environment. Unfortunately, the recycling industry grapples with persistent challenges, primarily in the realm of accurate trash classification, a critical factor for successful recycling. Manual sorting, often prone to errors due to subjective human judgment, hampers the recycling process, contributing to inefficiencies. Furthermore, the inherent risks associated with direct contact during the sorting of hazardous materials pose serious health concerns for the workers involved. In response to these challenges, we propose a revolutionary solution: the Trash Classification and Recycling Assistant utilizing YOLO variants V5-V7. This system, rooted in image classification techniques, seeks to elevate the precision of trash sorting. Notably, YOLO variant V7 emerges as the frontrunner, showcasing remarkable accuracy improvements. By harnessing the capabilities of advanced technology, this innovative approach not only streamlines waste sorting processes but also mitigates health risks linked to manual handling of toxic materials. The integration of YOLO variants V5-V7 represents a pivotal step towards ushering in a new era of efficiency and accuracy in recycling practices, thus significantly contributing to the overarching goal of environmental sustainability.

Zenodo (CERN European Organization for Nuclear Research)
Responsible consumption and production
Openalex Percentile: Top 44%
Plant chemical constituents analysis
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