@Article{cmes.2022.020793,
AUTHOR = {Saied M. Abd El-atty, Nancy A. Arafa, Atef Abouelazm, Osama Alfarraj, Konstantinos A. Lizos, Farid Shawki},
TITLE = {Performance Analysis of an Artificial Intelligence Nanosystem with Biological Internet of Nano Things},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {133},
YEAR = {2022},
NUMBER = {1},
PAGES = {111--131},
URL = {http://www.techscience.com/CMES/v133n1/48850},
ISSN = {1526-1506},
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.},
DOI = {10.32604/cmes.2022.020793}
}