IoT Based Edge Framework Industry 4.0 Using Block Chain and Deep Learning Models

Vinoth Kumar B., Monisha K., M. M. Arun Prasath, Vasanth M., M. S. Vijayaraj, Bharath Karthick K. A.

2025

Abstract

Aim: The aim of study is to design a high gain novel combining blockchain and deep learning to enhance manufacturing and industrial processes by capturing and analyzing real-time industrial data with high accuracy and secure logging of data. Materials and Methods: In this research, there are two groups. Group 1: Long Short- Term Memory (LSTM)-detecting machine failures before they happen with long response time. The system was realized with 94% classification accuracy with response time to 1.2 seconds. Group 2: Blockchain technology with LSTM provides predictive maintenance data, tamper- proof quality control and privacy and security. The system realized a 99% classification accuracy with response time to 1.2 seconds. Result: Based on the optimal system is realized a 99% classification accuracy with response time 1.2 seconds. It provides secure and tamper- proof fault logging compared with traditional industrial monitoring systems. The significance of about 0.015. Conclusion: In this work, it is observed that the tamper- proof mechanism with deep learning has significantly better accuracy and security compared with LSTM using fault detection.

Paper Citation

in Harvard Style

B. V., K. M., Prasath M., M. V., Vijayaraj M. and A. B. (2025). IoT Based Edge Framework Industry 4.0 Using Block Chain and Deep Learning Models. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 757-764. DOI: 10.5220/0013905100004919

in Bibtex Style

@conference{icrdicct`2525,
author={Vinoth B. and Monisha K. and M. Prasath and Vasanth M. and M. Vijayaraj and Bharath A.},
title={IoT Based Edge Framework Industry 4.0 Using Block Chain and Deep Learning Models},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={757-764},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013905100004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - IoT Based Edge Framework Industry 4.0 Using Block Chain and Deep Learning Models
SN - 978-989-758-777-1
AU - B. V.
AU - K. M.
AU - Prasath M.
AU - M. V.
AU - Vijayaraj M.
AU - A. B.
PY - 2025
SP - 757
EP - 764
DO - 10.5220/0013905100004919
PB - SciTePress