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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM40491
Volume:
9 |
1 |
Jan 2025
Pages:
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.
Efficient waste management is crucial for sustainable urban living. However, challenges such as improper segregation, low recycling rates, and reliance on manual systems hinder progress toward environmental goals. This paper introduces EcoSort AI, an AI-driven waste management solution that combines computer vision, IoT technologies, and machine learning to automate and optimize waste segregation. Leveraging convolutional neural networks (CNNs), the system identifies, classifies, and sorts waste materials into appropriate categories, ensuring improved recycling rates and reduced landfill burden. EcoSort AI features IoT-enabled smart bins for real-time classification and integrates seamlessly into existing urban infrastructures. Experimental results demonstrate significant improvements in sorting accuracy, efficiency, and public engagement.
KEYWORDS
Publication Date
1/13/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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