Open Access

ARTICLE

Blockchain-Enabled AI Recommendation Systems Using IoT-Asisted Trusted Networks

Mekhled Alharbi^1,*, Khalid Haseeb², Mamoona Humayun^3,*

1 Department of Software Engineering, College of Computer and Information Sciences, Jouf University, Sakaka, 72341, Al-Jouf, Saudi Arabia
2 Department of Computer Science, Islamia College Peshawar, Peshawar, 25120, Pakistan
3 School of Computing, Engineering and the Built Environment, University of Roehampton, London, SW15 5PU, UK

* Corresponding Authors: Mekhled Alharbi. Email: ; Mamoona Humayun. Email:

(This article belongs to the Special Issue: Recent Advances in Blockchain Technology and Applications)

Computers, Materials & Continua 2026, 87(2), 21 https://doi.org/10.32604/cmc.2025.073832

Received 26 September 2025; Accepted 11 December 2025; Issue published 12 March 2026

Abstract

The Internet of Things (IoT) and cloud computing have significantly contributed to the development of smart cities, enabling real-time monitoring, intelligent decision-making, and efficient resource management. These systems, particularly in IoT networks, rely on numerous interconnected devices that handle time-sensitive data for critical applications. In related approaches, trusted communication and reliable device interaction have been overlooked, thereby lowering security when sharing sensitive IoT data. Moreover, it incurs additional energy consumption and overhead while addressing potential threats in the dynamic environment. In this research, an Artificial Intelligence (AI) recommended fault-tolerant framework is proposed that leverages blockchain technology, aiming to enhance device trustworthiness and ensure data privacy. In addition, the intelligence of the proposed framework enables more authentic and authorized device involvement in data routing, thereby enabling seamless transmission in smart cities integrated with lightweight computing. To evaluate dynamic network conditions, the proposed framework offers a timely decision-making system to ensure robust delivery of IoT-assisted services. Using simulations, the efficacy of the proposed framework is validated by comparing it with existing approaches across various network metrics, demonstrating remarkable performance while achieving energy efficiency and optimizing network resources.

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Keywords

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