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This paper examines the integration of fog computing in current RPM systems with a focus on latency and real-time response capabilities. Unlike typical cloud models, fog computing layers computation closer to the edge devices therefore enhancing decentralization. This work provides an overview of how fog layers are incorporated in RPM for data pre-processing, context computations, and security. These are features such as the ability to generate rules dynamically, facilitating high accuracy of the health status determined by physiological, behavioral as well as environmental parameters. With the help of the implemented context-aware access control (CAAC) mechanism, which is backed up by the utilization of public key infrastructure, data security is reached. The design strategy discussed in this paper and implemented using NS-2 shows enhanced performance not only in relationships of packet delivery ratio, throughput, and end-to-end delay but also in other important measures. The comparative analysis shows that the integration of fog computing improves system performance, in media transmission, and responses are computed faster than those of cloud-only solutions. These discoveries strengthen the impact of fog computing to overcome latency, scalability, and security issues in IoT-based healthcare systems making it an enabler of real-life, life-critical applications.
Poddar et al. (Wed,) studied this question.