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  3. Autonomous Waste Classification Using Multi-agent Systems And Blockchain: A Low-cost Intelligent Approach.
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  3. Autonomous Waste Classification Using Multi-agent Systems And Blockchain: A Low-cost Intelligent Approach.

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Autonomous Waste Classification Using Multi-Agent Systems and Blockchain: A Low-Cost Intelligent Approach.

Sergio García González1, David Cruz García1, Rubén Herrero Pérez1

  • 1Expert Systems and Applications Laboratory, Faculty of Science, University of Salamanca, 37008 Salamanca, Spain.

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|July 30, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces a smart bin using AI and blockchain for automatic waste sorting. The system efficiently classifies waste, enhancing sustainability and transparency in smart cities.

Keywords:
blockchainintelligent classificationmulti-agent systemssmart waste management

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Area of Science:

  • Environmental Science
  • Computer Science
  • Artificial Intelligence

Background:

  • Growing global waste generation necessitates advanced, sustainable waste management solutions.
  • Current waste management systems often lack efficiency and transparency, hindering effective recycling and resource recovery.

Purpose of the Study:

  • To develop and implement a prototype smart bin for automated waste sorting.
  • To integrate a multi-agent system and blockchain technology for intelligent waste classification and transparent data management.

Main Methods:

  • Utilized sensors for waste identification (organic, plastic, paper).
  • Employed a multi-agent system for collaborative, real-time sorting decisions.
  • Integrated blockchain for immutable and transparent waste registration and traceability.
  • Evaluated YOLOv8, YOLOv11, and YOLOv12 for waste detection and classification, selecting YOLOv12 based on performance.

    • Main Results:

    • YOLOv12 demonstrated superior performance with mAP@50 of 86.2%, 84.6% overall accuracy, and 80.1% F1 score.
    • Achieved processing latency below 9 ms per image with YOLOv12, enabling near-real-time application.
    • The smart bin prototype confirmed viability in accuracy and computational efficiency.

    Conclusions:

    • The developed smart bin offers an innovative, cost-effective, and scalable solution for ambient intelligence in waste management.
    • This system lays the groundwork for smart waste management infrastructures in sustainable urban environments.
    • The integration of AI and blockchain enhances waste sorting efficiency, traceability, and transparency.