The rapid evolution of the Internet of Nano Things (IoNT) and Fog Computing presents new opportunities for creating advanced smart systems that are both efficient and responsive. Integrating IoNT with Fog Computing offers a powerful paradigm that can address the limitations of cloud-centric architectures, particularly in terms of latency, bandwidth, and real-time processing. The paper explores the synergistic combination of IoNT and Fog Computing, focusing on the development of a hybrid architecture that leverages the proximity and computational capabilities of fog nodes to process data generated by nanoscale devices. Key challenges such as resource management, data processing efficiency, and security concerns are addressed in this study. The proposed architecture not only enhances the performance of smart systems by reducing latency and optimizing resource utilization but also ensures robust security and privacy for the vast amounts of generated data. A comprehensive dataset was generated to assess the integration of the IoNT with Fog Computing, focusing on environmental parameters such as Temperature, Humidity, and Wind Speed, as collected from five IoNT sensors. Python was employed to generate and augment this dataset, ensuring the accurate representation of varied environmental conditions. The data transmission between IoNT sensors and FogNode_1 successfully demonstrated the framework’s ability to capture and process real-time environmental information. Aggregated data from the fog and cloud layers confirmed the system’s efficiency in reducing latency and maintaining data integrity. Furthermore, the implementation of advanced communication protocols and effective resource management highlights the robustness of the integration, contributing to the real-time monitoring and decision-making processes in environmental applications. As well as, this study compares Fog Computing and Cloud Computing, concluding that Fog Computing offers significant advantages in areas like latency, bandwidth utilization, resource efficiency, security, privacy, real-time processing, and edge intelligence. These benefits make Fog Computing particularly suitable for applications requiring low latency, local data processing, enhanced security, and the ability to leverage edge intelligence. While Cloud Computing may have advantages in certain areas, Fog Computing’s overall performance and versatility make it a compelling choice for those seeking to optimize their computing infrastructure. This research aims to pave the way for more resilient and intelligent smart systems that can operate effectively in various domains, including healthcare, environmental monitoring, and industrial automation.

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