A Study on AI-driven IoT (AIIoT) based Decision Making: KSK Approach in Robot for Medical Applications

Abstract

Robots are incredibly effective in various medical settings. Robots can potentially transform healthcare in multiple ways, including surgery, rehabilitation, medication discovery, and diagnostics. Future medical robot applications should grow more innovative as technology advances, resulting in better patient outcomes and a more efficient healthcare system. There are various ways in which Internet of Things-powered robots might transform the healthcare sector. Medical practitioners employ these robots as valuable instruments for telemedicine, surgery, medication delivery, and rehabilitation. While some obstacles can be overcome, the advantages of deploying IoT-based robots in healthcare exceed the disadvantages. As technology improves, we should expect to see even more creative applications of these robots in the medical field, enhancing the quality and efficacy of healthcare services. The introduction of AI-driven Internet of Things (AIIoT) decision-making (KSK method) in robots has drastically altered the healthcare landscape. Decision-making in Robots like these improves patient care, fills gaps in the healthcare system, and relieves medical staff of some of their job. As research and development in this field progresses, we may expect more medical applications for these robots, which will transform the healthcare industry. The employment of robots in various medical applications has grown more practical as the robotics industry has integrated AI and IoT technology. These robots can improve healthcare delivery, reduce costs, and improve patient outcomes. There are hazards inherent with any new technology. Still, AI-driven Internet of Things (IoT) based decision-making (KSK method) in robots can significantly advance medicine if adequately controlled and implemented.