Waste mismanagement, particularly the improper segregation of trash, is a critical environmental issue that undermines wasteprocessing efficiency and exacerbates pollution. Despite numerous initiatives aimed at promoting waste segregation, many individuals continue to struggle with correctly categorizing waste into biodegradable and non-biodegradable components. This study addresses this challenge by developing the SMARTSEGBIN, an automatic segregation bin designed specifically forclassroom environments. The research aims to design and develop an AI-trainable trash bin for classrooms. It also compares the accuracy of SMARTSEGBIN with the manual waste segregation methods. Furthermore, it evaluates the effectiveness of the binin educating students about waste categorization. The findings reveal that the SMARTSEGBIN utilizes AI technology effectively, achieving high accuracy in distinguishing between biodegradable and non-biodegradable waste. This significant enhancement in accuracy compared to manual segregation methods demonstrates the potential for AI-assisted systems to improve the reliability and efficiency of waste management practices. Additionally, the SMARTSEGBIN proves to be an effective educational tool, resulting in substantial increases in users ability to identify waste categories, their confidence inmaking disposal decisions, and their awareness of the environmental impacts of improper waste handling. Engaging with the SMARTSEGBIN not only provides educational benefits but also fosters a culture of responsible waste disposal among students, encouraging sustainable practices that positively impact both the school and the broader community.

smart bin

AI

trainable

waste

segregation