Smart Health and IoMT

Continuous improvement of cost-effective healthcare and patient treatment is by far the top national interest worldwide. The proliferation, versatility, and agility of medical devices have revolutionized healthcare and contributed to the new smart Health (sHealth) era of internet of medical things (IoMT). Broadly speaking, these IoMT devices include wearable, miniaturized, or implantable sensors that can be efficiently used for patient monitoring. The recent pandemic has also triggered the need for new solutions and systems for smart and secure remote patient monitoring, and medical data exchange across multiple healthcare entities to help combat the outbreak.

The smart IoT systems research group (SIoTS-RG) focuses on developing innovative smart health architectures leveraging edge computing and machine learning for efficient medical data delivery and communication across different networking technologies. The group focuses on developing and implementing state-of-the-art AI techniques, at different system levels, that aggregate, process, and optimize the acquired data, in order to provide effective real-time management of medical data flows with high reliability. In particular, they developed smart AI techniques, including machine learning and reinforcement learning for optimal IoT device's resource utilization, including efficient energy consumption and improving computation of the vitals signs for efficient delivery. The group also focuses on leveraging emerging technologies such as Blockchain to facilitate efficient, secure, and QoS-aware medical data exchange across multiple healthcare stakeholders.