Artificial Intelligence and IoT for Smart Waste Management: Challenges, Opportunities, and Future Directions

Indonesia’s waste management system struggles to keep pace with rapid population growth and urbanization, resulting in inefficient waste collection, environmental degradation, and low recycling rates. The country predominantly relies on open dumping and landfilling, which contribute significantly to pollution and greenhouse gas emissions. This study explores the transformative role of Artificial Intelligence (AI) and the Internet of Things (IoT) in waste management, focusing on smart waste collection, automated sorting, real-time monitoring, and predictive analytics. AI-driven waste classification enhances recycling efficiency, while IoT-enabled smart bins optimize collection routes, reducing operational costs and landfill dependency. Despite these advantages, challenges such as high implementation costs, digital infrastructure limitations, and data privacy concerns hinder widespread adoption. This study highlights that policy support, investment in digital infrastructure, and stakeholder collaboration are crucial for successful implementation. By leveraging AI and IoT, Indonesia can significantly improve waste management efficiency, minimize environmental impact, and advance circular economy initiatives. The findings suggest that, with the right policies and investments, AI-driven waste management can drive sustainability, reduce waste mismanagement, and promote resource optimization, making it a vital strategy for future urban development in Indonesia.

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Publication Details

Journal
Journal of Future Artificial Intelligence and Technologies
Published
2025-04-06
DOI
https://doi.org/10.62411/faith.3048-3719-85
Citations
10
Primary Topic
Municipal Solid Waste Management
Type
article
Field-Weighted Citation Impact
9.97
Controls
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article

Artificial Intelligence and IoT for Smart Waste Management: Challenges, Opportunities, and Future Directions

Sameh Fuqaha, Nursetiawati Nursetiawati
10 citations
Journal of Future Artificial Intelligence and Technologies
Municipal Solid Waste Management
9.97
article

Artificial Intelligence and IoT for Smart Waste Management: Challenges, Opportunities, and Future Directions

Sameh Fuqaha, Nursetiawati Nursetiawati
article en
10 citations

Abstract

Indonesia’s waste management system struggles to keep pace with rapid population growth and urbanization, resulting in inefficient waste collection, environmental degradation, and low recycling rates. The country predominantly relies on open dumping and landfilling, which contribute significantly to pollution and greenhouse gas emissions. This study explores the transformative role of Artificial Intelligence (AI) and the Internet of Things (IoT) in waste management, focusing on smart waste collection, automated sorting, real-time monitoring, and predictive analytics. AI-driven waste classification enhances recycling efficiency, while IoT-enabled smart bins optimize collection routes, reducing operational costs and landfill dependency. Despite these advantages, challenges such as high implementation costs, digital infrastructure limitations, and data privacy concerns hinder widespread adoption. This study highlights that policy support, investment in digital infrastructure, and stakeholder collaboration are crucial for successful implementation. By leveraging AI and IoT, Indonesia can significantly improve waste management efficiency, minimize environmental impact, and advance circular economy initiatives. The findings suggest that, with the right policies and investments, AI-driven waste management can drive sustainability, reduce waste mismanagement, and promote resource optimization, making it a vital strategy for future urban development in Indonesia.

Journal of Future Artificial Intelligence and TechnologiesVol. 2(1)
Muhammadiyah University of Yogyakarta (ID)
Openalex Percentile: Top 2%
Municipal Solid Waste Management
9.97
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