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Related Experiment Videos

PoPI: A machine learning-based consensus mechanism for blockchain-enabled IoT systems.

Mubtasim Kamal Dihan1, Abdullah1, Amina1

  • 1Department of Computer Science and Engineering, Islamic University of Technology, Gazipur, Bangladesh.

Plos One
|April 13, 2026
PubMed
Summary
This summary is machine-generated.

We introduce Proof of Periodic Inference (PoPI), a novel machine learning consensus mechanism for Internet of Things (IoT) systems. PoPI enhances scalability and reliability in blockchain-based IoT networks.

Related Experiment Videos

Area of Science:

  • Computer Science
  • Distributed Systems
  • Machine Learning

Background:

  • Conventional Internet of Things (IoT) architectures face scalability and reliability issues due to centralized data processing.
  • Integrating blockchain with IoT offers solutions but faces challenges with existing consensus mechanisms on resource-constrained devices.
  • Existing consensus protocols are often unsuitable for the dynamic and resource-limited nature of IoT environments.

Purpose of the Study:

  • To propose a novel consensus mechanism, Proof of Periodic Inference (PoPI), specifically designed for blockchain-based IoT systems.
  • To address the limitations of centralized IoT architectures and unsuitable consensus mechanisms for IoT devices.
  • To enhance the scalability, reliability, and applicability of blockchain in dynamic IoT environments.

Main Methods:

  • Developed Proof of Periodic Inference (PoPI), a machine learning model-based consensus mechanism.
  • Utilized a supervised machine learning model for periodic selection of block producers.
  • Incorporated static and dynamic device features (e.g., battery level, resource usage) for reliable node selection.
  • Implemented fair participation mechanisms to ensure balanced network involvement.

Main Results:

  • PoPI demonstrates high scalability, suitable for large-scale IoT deployments.
  • The proposed mechanism achieves low latency, crucial for real-time IoT applications.
  • Experimental evaluations show improved applicability compared to existing state-of-the-art consensus protocols in dynamic IoT settings.

Conclusions:

  • Proof of Periodic Inference (PoPI) offers an effective solution for blockchain-based IoT systems.
  • The machine learning-based approach enhances consensus efficiency and reliability in dynamic IoT environments.
  • PoPI presents a promising advancement for overcoming the limitations of traditional IoT architectures and consensus mechanisms.