EW YOLO: Edge Computing IoT and YOLOv11 Setup for E-Waste

An industry 5.0 revolution is characterized by advanced automation and human-centric design resulting in an unprecedented growth in the electronics sector. This advancement comes at the cost of a surge in electronic waste (E-waste) generation. In the past, many researchers have reported on E-waste recycling and management; however, the efficient collection of domestic E-waste still remains a critical challenge. This research paper presents a novel approach to domestic E-waste management by developing a smart E-Bin equipped with an Electronic Waste Detection and Bin-Level Control System (EDBLCS), IoT setup, and a YOLOv11-powered (EW YOLO) computer vision system. This innovative solution selectively collects only E-waste, ensuring accurate identification and preventing contamination with other waste streams, with the [email protected] score increased to 0.90074 by Epoch 50, while [email protected]–0.95 reached 0.73899 using YOLOv11. The primary contribution of this work is the integration of YOLOv11-based real-time detection with an IoT-enabled smart E-Bin framework to enable selective, edge-oriented domestic E-waste segregation.

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Publication Details

Journal
Applied Sciences
Published
2026-02-23
DOI
https://doi.org/10.3390/app16042152
Primary Topic
Recycling and Waste Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

EW YOLO: Edge Computing IoT and YOLOv11 Setup for E-Waste

Munish Vashishath, Rashmi Chawla, Shubhyansh Rai
Applied Sciences
Recycling and Waste Management Techniques
article

EW YOLO: Edge Computing IoT and YOLOv11 Setup for E-Waste

Munish Vashishath, Rashmi Chawla, Shubhyansh Rai
article en

Abstract

An industry 5.0 revolution is characterized by advanced automation and human-centric design resulting in an unprecedented growth in the electronics sector. This advancement comes at the cost of a surge in electronic waste (E-waste) generation. In the past, many researchers have reported on E-waste recycling and management; however, the efficient collection of domestic E-waste still remains a critical challenge. This research paper presents a novel approach to domestic E-waste management by developing a smart E-Bin equipped with an Electronic Waste Detection and Bin-Level Control System (EDBLCS), IoT setup, and a YOLOv11-powered (EW YOLO) computer vision system. This innovative solution selectively collects only E-waste, ensuring accurate identification and preventing contamination with other waste streams, with the [email protected] score increased to 0.90074 by Epoch 50, while [email protected]–0.95 reached 0.73899 using YOLOv11. The primary contribution of this work is the integration of YOLOv11-based real-time detection with an IoT-enabled smart E-Bin framework to enable selective, edge-oriented domestic E-waste segregation.

Applied SciencesVol. 16(4)
University of Calabria (IT), J.C. Bose University of Science & Technology, YMCA (IN), Gautam Buddha University (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 44%
Recycling and Waste Management Techniques
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