Artificial Intelligence in Waste Sorting: Advancing Recycling Processes in Greece Through Ai-Driven Solutions

The integration of Artificial Intelligence (AI) in waste sorting presents a transformative opportunity to enhance recycling processes, addressing inefficiencies and environmental challenges. This study investigates the application of AI-driven technologies within Greece, focusing on improving material classification, reducing contamination, and optimizing waste management practices. By leveraging advanced image recognition, machine learning algorithms, and robotic systems, the research demonstrates AI's potential to overcome infrastructure deficiencies and high operational costs, while fostering sustainability. A comprehensive analysis identifies socio-economic and environmental benefits, evaluates current barriers, and proposes a scalable framework for AI implementation. The findings aim to guide policymakers, industry stakeholders, and environmental organizations in adopting AI as a pivotal tool for advancing waste management and achieving global sustainability targets.

Authors

Institutions

Publication Details

Journal
International Journal of Clinical Case Reports and Reviews
Published
2025-02-04
DOI
https://doi.org/10.31579/2690-4861/697
Citations
1
Primary Topic
Recycling and Waste Management Techniques
Type
article
Field-Weighted Citation Impact
1.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence in Waste Sorting: Advancing Recycling Processes in Greece Through Ai-Driven Solutions

Paraschos Maniatis
1 citations
International Journal of Clinical Case Reports and Reviews
Recycling and Waste Management Techniques
1.00
article

Artificial Intelligence in Waste Sorting: Advancing Recycling Processes in Greece Through Ai-Driven Solutions

Paraschos Maniatis
article en
1 citations

Abstract

The integration of Artificial Intelligence (AI) in waste sorting presents a transformative opportunity to enhance recycling processes, addressing inefficiencies and environmental challenges. This study investigates the application of AI-driven technologies within Greece, focusing on improving material classification, reducing contamination, and optimizing waste management practices. By leveraging advanced image recognition, machine learning algorithms, and robotic systems, the research demonstrates AI's potential to overcome infrastructure deficiencies and high operational costs, while fostering sustainability. A comprehensive analysis identifies socio-economic and environmental benefits, evaluates current barriers, and proposes a scalable framework for AI implementation. The findings aim to guide policymakers, industry stakeholders, and environmental organizations in adopting AI as a pivotal tool for advancing waste management and achieving global sustainability targets.

International Journal of Clinical Case Reports and ReviewsVol. 23(1)
Athens University of Economics and Business (GR)
Openalex Percentile: Top 26%
Recycling and Waste Management Techniques
1.00
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.