Soft computing-enabled fuzzy-based approach to design access control mechanism for tele-robotic surgeries

The application of soft computing techniques in tele-robotic surgery can offer various benefits such as enhancing the precision of robotic systems, reducing the impact of communication delays, and improving the safety and efficacy of surgical procedures. Fuzzy logic is used in this research to model the uncertain and imprecise nature of surgical data and to provide decision-making support for the surgical robot. Tele-robotic systems are being widely used for automated surgeries, medication, and diagnostics. As these technologies involve internet-connected devices, it is important to establish trust between them and implement access control methods to enhance security and usability. The proposed fuzzy-based approach improves energy efficiency and effectively assigns access rights while performing tele-robotic surgeries. Machine intelligence-based fuzzy logic is used to guide the robotic arm during surgery and to adjust the forces exerted by the robot based on the softness or hardness of the tissues being operated on. These systems also provide data security and low latency and secure communication solutions for the tele-robotics community. The proposed machine intelligence-based mechanism performs activities independently and intelligently to minimize the latency in response, to optimize the energy consumed during communication. To assign permissions based on the least privileges, the proposed fuzzy intelligence-based algorithm is developed, and its performance is evaluated in terms of denial of service, throughput, latency in response, and energy consumption. The simulated results reveal that the proposed FACM approach can achieve good throughput, minimize latency and optimize energy consumption during tele-robotic surgeries.