AI-Driven Wireless Communication for Remote Surgery: Enabling Ultra-Reliable and Low-Latency Healthcare Systems

About the Project

This doctoral research explores the integration of Artificial Intelligence and next-generation wireless communication to enable remote and robotic surgery with ultra-reliable and low-latency connectivity.

Remote surgery is a transformative application in 6G-enabled healthcare, empowering surgeons to perform precise operations from distant locations using robotic systems. Achieving this safely and efficiently demands innovations in communication architecture, intelligent network management, and data security.

This project seeks to design and evaluate AI-empowered wireless communication frameworks that ensure precision, reliability, and sustainability in real-time surgical environments.

Research Objectives

• Develop AI-assisted wireless communication models for ultra-reliable low-latency connections.
• Design intelligent resource allocation and adaptive network optimization for surgical operations.
• Investigate energy-efficient and secure transmission of medical data.
• Integrate edge and cloud computing for real-time surgical decision support.
• Create simulation environments to test performance under realistic healthcare conditions.

Methodology

• Comprehensive Review: Examine current developments in remote healthcare, 6G networks, and AI-based optimization.
• System Design: Build communication frameworks powered by deep learning and intelligent edge computing.
• Testing and Evaluation: Simulate and analyze network performance for latency, accuracy, and data security.
• Ethics and Privacy: Incorporating ethical safeguards and data protection principles in all stages.

Impact

This project aims to redefine digital healthcare by enabling safe and reliable remote surgical systems through intelligent communication design. Combining Artificial Intelligence, wireless engineering, and medicine, it aspires to create equitable access to expert medical care worldwide, even in resource-limited regions.

Funding Notes

there is no funding for this project