Smart City Gnosys

Smart city article details

Title	Ai-Driven Iot-Fog Analytics Interactive Smart System With Data Protection
ID_Doc	7028
Authors	Haseeb K.; Saba T.; Rehman A.; Abbas N.; Kim P.W.
Year	2025
Published	Expert Systems, 42, 1
DOI	http://dx.doi.org/10.1111/exsy.13573
Abstract	In recent decades, fog computing has contributed significantly to the expansion of smart cities. It generated numerous real-time data and coped with time-constraint applications. They use sensors, physical objects, and network standards to monitor health imaging, traffic surveillance, industrial management, and so forth. Interactive applications have been proposed for the Internet of Things (IoT) to control wireless channels and improve communication. However, most of the existing lack of handing network interference and a reliable monitoring process. Moreover, many solutions are vulnerable to external threats, resulting in inconsistent and untrustworthy information for end users. Thus, this article proposes a framework that considers possible shortest paths to provide the most reliable and low-latency healthcare decision system using Q-learning. In addition, fog devices offer a trusted transmission interference system and are kept secure. The proposed framework is specially designed for rapid real-time medical data processing while enforcing robust security throughout the IoT-based transmission process. To identify the health sensors in pairwise objects with the initial computing cost, the proposed framework applies graph theory. It also extracts the most effective and least loaded communication edges by examining the behaviour of devices. Moreover, the identities of devices are verified using lightweight timestamps and secret information, accordingly, it decreases the privacy threats. © 2024 John Wiley & Sons Ltd.
Author Keywords	healthcare; image; mobile intelligence; reliable processing; smart systems

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