International Transactions on Artificial Intelligence (ITALIC)
Vol. 2 No. 2 (2024): International Transactions on Artificial Intelligence

AI as a Driver of Efficiency in Waste Management and Resource Recovery

Li Wei Ming (Ijiis Incorporation)
James Anderson (Pandawan Incorporation)
Farhan Hidayat (University of Raharja)
Firdaus Dwi Yulian (University of Raharja)
Nanda Septiani (Association of Colleges of Informatics and Computer Science)



Article Info

Publish Date
21 Jun 2024

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.

Copyrights © 2024






Journal Info

Abbrev

italic

Publisher

Subject

Computer Science & IT Control & Systems Engineering Library & Information Science

Description

International Transactions on Artificial Intelligence (ITALIC) is an international, open-access journal established to publish groundbreaking research in the field of Artificial Intelligence (AI). ITALIC focuses on both theoretical and experimental AI research and explores its applications across ...