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Performance Analysis of an Artificial Intelligence Nanosystem with Biological Internet of Nano Things

Saied M. Abd El-atty1,*, Nancy A. Arafa1, Atef Abouelazm1, Osama Alfarraj2, Konstantinos A. Lizos3, Farid Shawki1

1 Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt
2 Computer Science Department, Community College, King Saud University, Riyadh, Saudi Arabia
3 Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo (UiO), Oslo, Norway

* Corresponding Author: Saied M. Abd El-atty. Email: email

(This article belongs to this Special Issue: Artificial Intelligence of Things (AIoT): Emerging Trends and Challenges)

Computer Modeling in Engineering & Sciences 2022, 133(1), 111-131. https://doi.org/10.32604/cmes.2022.020793

Abstract

Artificial intelligence (AI) has recently been used in nanomedical applications, in which implanted intelligent nanosystems inside the human body were used to diagnose and treat a variety of ailments with the help of the Internet of biological Nano Things (IoBNT). Biological circuit engineering or nanomaterial-based architectures can be used to approach the nanosystem. In nanomedical applications, the blood vascular medium serves as a communication channel, demonstrating a molecular communication system based on flow and diffusion. This paper presents a performance study of the channel capacity for flow-based-diffusive molecular communication nanosystems that takes into account the ligand-receptor binding mechanism. Unlike earlier studies, we take into account the effects of biological physical characteristics such as blood pressure, blood viscosity, and vascular diameter on channel capacity. Furthermore, in terms of drug transmission error probability, the inter-symbol interference (ISI) phenomenon is applied to the proposed system. The numerical results show that the proposed AI nanosystems-based IoBNT technology can be successfully implemented in future nanomedicine.

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Cite This Article

M., S., Arafa, N. A., Abouelazm, A., Alfarraj, O., Lizos, K. A. et al. (2022). Performance Analysis of an Artificial Intelligence Nanosystem with Biological Internet of Nano Things. CMES-Computer Modeling in Engineering & Sciences, 133(1), 111–131.



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