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

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.