Intelligent system design for bionanorobots in drug delivery

Area of Science:

• Biomedical Engineering
• Nanotechnology
• Artificial Intelligence

Background:

• Nanorobots are smart nanoscale structures with actuation, sensing, manipulation, intelligence, and swarm capabilities.
• Cancer diagnosis and treatment remain significant challenges in medicine.

Purpose of the Study:

• To design an intelligent system for tumor diagnosis and treatment using bionanorobots.
• To utilize fuzzy logic for interpreting uncertain sensory information from nanosensors.
• To develop robust drug delivery mechanisms for cancer therapy.

Main Methods:

• Designed an intelligent system integrating fuzzy logic with thermal, magnetic, optical, and chemical nanosensors.
• Implemented two distinct fuzzy logic structures: Mamdani for diagnosis and Takagi-Sugeno for treatment.
• Validated the system's performance using simulated conditions, assessing drug delivery robustness.

Main Results:

• The fuzzy logic system effectively interpreted uncertain sensory data from nanosensors.
• The Mamdani structure accurately diagnosed tumors, while the Takagi-Sugeno structure optimized drug delivery.
• Bionanorobot drug delivery demonstrated robustness against sensor noise during navigation, diagnosis, and treatment.

Conclusions:

• Intelligent bionanorobots equipped with fuzzy logic offer a promising approach for cancer therapy.
• The designed system provides a reliable method for targeted tumor treatment.
• Bionanorobots hold significant potential for advancing future cancer treatment strategies.