Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey

Maysaa Salama

doi:10.35377/saucis...1582663

EN

Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey

Abstract

This extensive research investigates the integration of blockchain, MQTT and machine learning on the Internet of Things (IoT), a field ripe for transformation with technologies. These three technologies are blockchain and Message Queuing Telemetry Transport (MQTT). Machine learning is a foundational pillar, each offering unique benefits to enhance data exchange, security and decision making in interconnected IoT environments. Our study aims to explore the synergies among these technologies and the implications of their combined usage on the IoT. I delve into how their integration strengthens data security, enables communication, and facilitates data-driven decision-making across IoT scenarios. The study examines types of blockchain technology and the significance of MQTT in IoT communication. Additionally, I explore the implementation of machine learning models. Our primary focus is on exploring how combining blockchain and MQTT can enhance data sharing. I address challenges such as privacy concerns, scalability issues and consensus processes. To illustrate the impact of this convergence, I present practical examples from industries like supply chain management, healthcare services, and finance. Furthermore, this research also encompasses themes such as interoperability, among systems standardization measures, edge computing applications, and privacy-oriented machine learning approaches.

Keywords

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Details

Primary Language

English

Subjects

Computer Software

Journal Section

Review

Authors

Maysaa Salama ^*
0009-0001-8381-0492
Türkiye

Early Pub Date

September 30, 2025

Publication Date

September 30, 2025

Submission Date

November 10, 2024

Acceptance Date

August 25, 2025

Published in Issue

Year 1970 Volume: 8 Number: 3

DOI

https://doi.org/10.35377/saucis...1582663

IZ

https://izlik.org/JA85ER42EF

Cite

RIS / Bibtex

APA

Salama, M. (2025). Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey. Sakarya University Journal of Computer and Information Sciences, 8(3), 570-591. https://doi.org/10.35377/saucis...1582663

AMA

1.Salama M. Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey. SAUCIS. 2025;8(3):570-591. doi:10.35377/saucis.1582663

Chicago

Salama, Maysaa. 2025. “Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey”. Sakarya University Journal of Computer and Information Sciences 8 (3): 570-91. https://doi.org/10.35377/saucis. 1582663.

EndNote

Salama M (September 1, 2025) Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey. Sakarya University Journal of Computer and Information Sciences 8 3 570–591.

IEEE

[1]M. Salama, “Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey”, SAUCIS, vol. 8, no. 3, pp. 570–591, Sept. 2025, doi: 10.35377/saucis...1582663.

ISNAD

Salama, Maysaa. “Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey”. Sakarya University Journal of Computer and Information Sciences 8/3 (September 1, 2025): 570-591. https://doi.org/10.35377/saucis. 1582663.

JAMA

1.Salama M. Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey. SAUCIS. 2025;8:570–591.

MLA

Salama, Maysaa. “Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey”. Sakarya University Journal of Computer and Information Sciences, vol. 8, no. 3, Sept. 2025, pp. 570-91, doi:10.35377/saucis. 1582663.

Vancouver

1.Maysaa Salama. Integrating Blockchain, MQTT, and Machine Learning for Enhanced IoT Applications: A Comprehensive Survey. SAUCIS. 2025 Sep. 1;8(3):570-91. doi:10.35377/saucis. 1582663