Design of Future Intelligent Healthcare Systems

Communication networks play a crucial role in the healthcare sector in delivering safe and mission-critical health services for patients. However, the currently deployed communications infrastructure is not designed to tackle the massive surge of patients due to pandemics such as the recent COVID-19 outbreak. That necessitates introducing new communication technologies that can foster remote patient treatment, such as remote robotic surgery, to limit surgeon-patient interaction. The tactile internet (TI), an evolutionary leap of the InternetofThings, is a telecommunications network that aims remotely control objects employing haptic communications. TI-enabled remote robotic surgery is a viable solution to separate the surgeon and the patient physically. Nevertheless, the TIenabled remote healthcare system imposes a strict requirement on the quality-of-services, such as ultra-high reliability of 99.99999% and ultra-low latency of 1 ms. It is noteworthy that the upcoming sixth-generation (6G) mobile technology will also focus on designing ultra-reliable and low-latency communication (URLLC) technology for mission-critical applications like TIenabled remote robotic surgery

The digital twin (DT) has become a game-changing technology in Supervisors should note that all projects must have at least two Ulster University supervisors and that priority in the main competition will be given to projects which include one new supervisor/ECR on the team. In addition, supervisors may only submit one Project Proposal per supervisory team for the main scholarship competition. many communications and healthcare sectors. Artificial intelligence/machine learning (AI/ML) has recently been used in DT to enhance the DT capabilities in accurately replicating the real-world scenario and the real-time prediction of the system states from past examples. This research work is envisioned designing an AI/ML-based DT framework for the 6G-enabled TI, focusing on URLLC technology to be applied for remote robotic surgery

The various stages of this research work include the design of the AI/ML-based DT framework for TI-enabled remote robotic surgery with a focus on URLLC and evaluating the proposed framework’s performance with existing techniques in the literature. Matlab/or Python will be employed for general system modelling, whereas TensorFlow/Keras will be adopted to implement the AI/ML models. The research outcomes are expected to be submitted for publication in various peer reviewed IEEE Transactions/journals.