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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65396
Volume:
10 |
6 |
Jun 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Department of electronics and telecommunication
Sinhgad College of engineering

Department of electronics and telecommunication
Sinhgad College of engineering

Department of electronics and telecommunication
Sinhgad College of engineering
Department of electronics and telecommunication
Sinhgad College of engineering
The increasing global concern for environmental sustainability has prompted the development of innovative tech-nologies aimed at optimizing waste management processes. In this context, the AI Audio Classify Recycle Bin emerges as a groundbreaking solution, leveraging artificial intelligence to enhance recycling practices. The system captures and analyzes audio signals produced by disposed items through integrated mi-crophones and classifies materials such as glass, plastic, metal, and paper based on their distinct sound signatures. This real-time, decentralized approach ensures efficient sorting directly within the bin, minimizing contamination and promoting proper recycling practices. With benefits including increased accuracy, environmental sustainability, reduced operational costs, and user-friendly interfaces, this technology represents a significant advancement toward a more environmentally conscious and effective waste management system.
KEYWORDS
The AI Audio Classify Recycle Bin project is an innovative and sustainable solution for modern waste management. By combining artificial intelligence with audio-based waste classifi-cation, it automates the process of waste segregation, improves recycling efficiency, and reduces environmental pollution. The system’s ability to operate entirely at the edge without relying on cloud connectivity makes it robust, fast, and suitable for deployment in diverse environments.
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Publication Date
6/24/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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