ABSTRACT
A rising range of Internet of Things (IoT) applications in the medical sector are referred to as medical IoT, also known as healthcare IoT. These give rise to a wide range of IoT products and services that are especially suited for healthcare scenarios and requirements, such as sensors and applications for telemedicine consultation and delivery, remote healthcare monitoring, and telehealth monitoring. Through numerous methods, like robotic surgery, enhanced diagnostics, and real-time patient monitoring, medical IoT can help patients receive better results. Through the use of telemedicine and other associated technological breakthroughs, Medical IoT (MIoT) is crucial in the increasingly decentralized nature of health and healthcare, which eliminates the necessity for in-person visits. Through enhanced automation, safety, and other technological advancements, medical IoT presents new potential for healthcare providers to enhance patient care and manage the inherently complicated nature of the healthcare industry. Traditional database management techniques fall short of meeting the complex application requirements of an IoT network with genuine global reach. The IoT environment is only partially addressed by current IoT data management solutions, with a particular emphasis on sensor networks. In this study, an overview of the data management approaches that are suggested for MIoT or IoT-related subsystems. The unique design primitives emphasized here should be handled in an IoT data management system and about how the suggested solutions handle them. Finally, the suggested IoT data management framework that incorporates the previously stated design components and serves as a foundation for an all-encompassing MIoT data management solution.
