@Article{cmc.2025.063077,
AUTHOR = {Khulud Salem Alshudukhi, Mamoona Humayun, Ghadah Naif Alwakid},
TITLE = {Integrating Edge Intelligence with Blockchain-Driven Secured IoT Healthcare Optimization Model},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {83},
YEAR = {2025},
NUMBER = {2},
PAGES = {1973--1986},
URL = {http://www.techscience.com/cmc/v83n2/60593},
ISSN = {1546-2226},
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.},
DOI = {10.32604/cmc.2025.063077}
}