EcoShreds: A 5-Class Image Dataset for Edge-AI Smart Waste Segregation and MobileNetV3 Optimization
Published: 3 August 2026| Version 1 | DOI: 10.17632/9n25xjfjcz.1
Contributor:
Richmond Owusu AgyeiDescription
This dataset contains 2,057 high-resolution images categorized into five distinct classes tailored for source-level municipal solid waste (MSW) segregation using low-power Edge-AI systems. The dataset was curated to train, validate, and deploy lightweight deep learning models, specifically optimized for the MobileNetV3 Small architecture, running on resource-constrained hardware such as the ESP32-CAM module. The primary objective of this dataset is to facilitate automated real-time waste classification at the point of disposal within smart bin infrastructure.
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Institutions
- Kwame Nkrumah University of Science and TechnologyAshanti, Kumasi
Categories
Computer Vision, Image Processing, Internet of Things