An AIoT Device for Raising Awareness About Trash Classification at Source

Waste segregation is a critical issue for environmental protection and sustainable growth. In Vietnam, public awareness and action on waste separation at source remain limited, highlighting the importance of engaging individuals, particularly students, in transforming waste disposal practices. Modern technologies, including the Internet of Things (IoT) and Artificial Intelligence (AI), have revolutionized various aspects of our lives and offer promising solutions to raise public awareness on this issue. This paper proposes an IoT device named BEG (BACHKHOA Eco-friendly Guide) integrating AI-based Computer Vision technology to classify waste via a camera. Unlike existing smart trash cans, which classify and dispose of the trash automatically, our device provides information about the waste type to guide users on proper disposal, thus reinforcing awareness of garbage classification at source. We also introduce the BEGNet, a Convolutional Neural Network (CNN) employing RegNetY120 as its backbone, which demonstrates superior performance in accuracy compared to other approaches on both the Trashnet dataset and our custom dataset - BKTrashImage. The proposed BEG device will improve knowledge about waste segregation, reduce improperly disposed waste, and foster a thriving circular economy.