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.
Authors
- Munish Vashishath
- Rashmi Chawla (ORCID: https://orcid.org/0000-0001-9816-6831)
- Shubhyansh Rai
Institutions
- University of Calabria (IT)
- J.C. Bose University of Science & Technology, YMCA (IN)
- Gautam Buddha University (IN)
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