Research Projects

The rapid evolution of modern communication paradigms and digital technologies is creating transformative opportunities for eHealth services. A significant proposal within future 6G networks is the incorporation of a biological layer, addressing the limitations of current healthcare systems in meeting the needs of an ever-growing population. This advancement heralds the Internet of Bio-Nano Things (IoBNT), a groundbreaking convergence of nanotechnology, biotechnology, and wireless communication. Traditional communication technologies (CT) are transitioning into molecular communication (MC) and terahertz (THz) communication, each offering unique advantages for IoBNT applications. MC utilizes molecules for nanoscale communication, while THz communication leverages high-frequency electromagnetic waves for sensing and interfacing with external systems. Together, these technologies enable robust communication links, bridging bio-nano systems and electromagnetic environments. One key challenge in pervasive healthcare is the insufficient concentration of biomarkers during the early stages of diseases, such as cancer, when symptoms are typically absent. This often delays diagnosis and treatment. By injecting bio-nanosensors, particularly in cases prone to relapse, even minimal biomarker concentrations can be effectively detected. These nanosensors, passing through the vicinity of cancerous tissue, provide critical diagnostic information. Molecular sensing facilitates reliable in-vivo detection, and THz waves efficiently convey this information to external systems, enabling a state-of-the-art diagnostic solution through the synergistic fusion of molecular and THz communication. Existing studies on in-vivo cancer diagnosis often employ simplified and abstract models for analytical ease, limiting their practical applicability. This project seeks to overcome these challenges by developing advanced blood vessel models that incorporate biomarker degradation and random release timing, significantly enhancing diagnostic accuracy. It aims to establish a cancer stage detection framework to distinguish healthy states from various cancer stages for precise disease characterization. For cancer tissue localization, the project will develop an innovative algorithm integrating distance estimation and machine learning, alongside a complementary range-free localization technique to enhance accuracy and robustness. Optimization of nanomachine release rates will be pursued to maximize drug delivery efficacy. Eventually, the project will analyze the attenuation characteristics of THz waves in biological tissues, such as skin, to evaluate their feasibility for interfacing MC systems with external devices. The project's outcomes promise transformative advancements in next-generation healthcare, delivering precise, efficient, and reliable solutions for early disease diagnosis and targeted therapy.