Open Access

ARTICLE

Integrating Edge Intelligence with Blockchain-Driven Secured IoT Healthcare Optimization Model

Khulud Salem Alshudukhi¹, Mamoona Humayun^2,*, Ghadah Naif Alwakid¹

1 Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka, 72388, Saudi Arabia
2 Department of Computing, School of Arts Humanities and Social Sciences, University of Roehampton, London, SW15 5PH, UK

* Corresponding Author: Mamoona Humayun. Email:

Computers, Materials & Continua 2025, 83(2), 1973-1986. https://doi.org/10.32604/cmc.2025.063077

Received 04 January 2025; Accepted 27 February 2025; Issue published 16 April 2025

Abstract

The Internet of Things (IoT) and edge computing have substantially contributed to the development and growth of smart cities. It handled time-constrained services and mobile devices to capture the observing environment for surveillance applications. These systems are composed of wireless cameras, digital devices, and tiny sensors to facilitate the operations of crucial healthcare services. Recently, many interactive applications have been proposed, including integrating intelligent systems to handle data processing and enable dynamic communication functionalities for crucial IoT services. Nonetheless, most solutions lack optimizing relaying methods and impose excessive overheads for maintaining devices’ connectivity. Alternatively, data integrity and trust are another vital consideration for next-generation networks. This research proposed a load-balanced trusted surveillance routing model with collaborative decisions at network edges to enhance energy management and resource balancing. It leverages graph-based optimization to enable reliable analysis of decision-making parameters. Furthermore, mobile devices integrate with the proposed model to sustain trusted routes with lightweight privacy-preserving and authentication. The proposed model analyzed its performance results in a simulation-based environment and illustrated an exceptional improvement in packet loss ratio, energy consumption, detection anomaly, and blockchain overhead than related solutions.

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Keywords

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