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All Journal International Transactions on Artificial Intelligence (ITALIC)
Nanda Septiani
Association of Colleges of Informatics and Computer Science
Computer Science & IT Control & Systems Engineering Library & Information Science

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AI as a Driver of Efficiency in Waste Management and Resource Recovery Li Wei Ming; James Anderson; Farhan Hidayat; Firdaus Dwi Yulian; Nanda Septiani
International Transactions on Artificial Intelligence Vol. 2 No. 2 (2024): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v2i2.547

Abstract

Effective waste management and resource recovery are essential for maintaining environmental sustainability. With the increasing volume of waste generated from industrial and domestic activities, there is a critical need for strategies that reduce environmental impact and enhance resource utilization efficiency. This study explores the application of artificial intelligence (AI) technologies, specifically Machine Learning (ML) and Artificial Neural Networks (ANN), in optimizing waste management processes. The research demonstrates that AI can significantly improve waste classification accuracy, predict waste volumes, and identify resource recovery opportunities. Implementing AI solutions resulted in a 15% increase in resource recovery efficiency and a 20% reduction in operational costs. These findings provide valuable insights for stakeholders and policymakers in integrating AI technologies to achieve more sustainable waste management practices.
Co-Authors Farhan Hidayat Firdaus Dwi Yulian James Anderson Li Wei Ming