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Related Experiment Videos

A Blockchain-Enhanced Neural Network Framework for secure e-waste forecasting in smart cities.

Jussen Facuy1,2, Ariel Pasini2, Elsa Estévez3

  • 1Universidad Agraria del Ecuador, Guayaquil, Guayas, Ecuador.

Frontiers in Public Health
|May 14, 2026
PubMed
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This summary is machine-generated.

Accurate electronic waste (e-waste) forecasting is crucial for smart cities. This study introduces a Blockchain-Enhanced Neural Network Framework (BENNF) for secure, transparent, and scalable e-waste prediction, integrating AI, big data, and blockchain.

Area of Science:

  • Environmental Science
  • Computer Science
  • Urban Planning

Background:

  • Exponential growth of electronic waste (e-waste) poses significant environmental challenges for urban areas.
  • Accurate e-waste generation forecasting is vital for sustainable urban planning and smart city initiatives.
  • Existing methods lack the necessary security, transparency, and scalability for effective e-waste management.

Purpose of the Study:

  • To propose a conceptual and architectural framework, the Blockchain-Enhanced Neural Network Framework (BENNF), for secure, transparent, and scalable e-waste forecasting.
  • To integrate artificial intelligence, big data analytics, and blockchain technology for enhanced environmental management.
  • To strengthen digital governance and trust in data-driven environmental decision-making within smart cities.
Keywords:
blockchainelectronic waste forecastingneural networkssecure data governancesmart cities

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Main Methods:

  • A three-layered framework: data acquisition/preprocessing (big data pipelines like Apache Spark/Hadoop), prediction (multilayer neural networks), and blockchain (smart contracts, Proof-of-Authority).
  • Utilizing socioeconomic and environmental variables for training neural networks.
  • Designing a system-level framework focused on digital governance and data integrity.

Main Results:

  • The BENNF framework offers a novel approach to e-waste forecasting by combining AI, big data, and blockchain.
  • Ensures data integrity, transparency, and traceability through blockchain technology.
  • Provides a scalable and adaptable model for urban contexts, exemplified by Guayaquil, Ecuador.

Conclusions:

  • BENNF enhances urban environmental management by providing reliable e-waste generation forecasts.
  • The framework supports Sustainable Development Goals (SDGs) 12 and 13, promoting circular economy and climate resilience.
  • BENNF represents a significant advancement in smart city initiatives for sustainable e-waste management.