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Blockchain based solid waste classification with AI powered tracking and IoT integration.

Aliaa M Alabdali1

  • 1Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, P. O. Box 344, 21911, Rabigh, Saudi Arabia. amalabdali@kau.edu.sa.

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This study introduces an AI-powered smart waste management system using IoT and Blockchain. It enhances waste classification and collection efficiency for sustainable urban environments.

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Area of Science:

  • Computer Science
  • Environmental Science
  • Engineering

Background:

  • Smart waste management is crucial for urban sustainability and environmental protection.
  • Current systems often lack real-time data processing and secure data handling capabilities.
  • Integration of advanced technologies is needed to optimize waste collection and recycling processes.

Purpose of the Study:

  • To develop and evaluate an AI-driven waste classification model for smart cities.
  • To integrate Internet of Things (IoT) and Blockchain technologies for efficient and secure waste management.
  • To improve waste sorting accuracy and optimize collection routes through intelligent decision-making.

Main Methods:

  • Utilizing IoT-enabled bins to collect real-time waste data.
  • Implementing Blockchain for secure, transparent, and immutable data storage.
  • Employing hybrid Machine Learning (ML) and Deep Learning (DL) algorithms for waste classification.
  • Assessing system performance using retrieval metrics and visualization tools.

Main Results:

  • The AI model demonstrates effective real-time waste classification.
  • Blockchain integration ensures data integrity and enhances transparency in waste management.
  • Hybrid ML and DL models show improved waste detection and sorting efficiency.
  • The system optimizes waste collection and recycling processes.

Conclusions:

  • The proposed AI-driven system significantly enhances smart waste management.
  • Integration of IoT, Blockchain, ML, and DL offers a robust solution for urban sustainability.
  • This intelligent approach improves operational efficiency and promotes environmental responsibility.