Empowering Healthcare Through IoMT: Unveiling the Architecture, Protocols, and Applications
DOI:
https://doi.org/10.37591/jomccmn.v10i2.651Keywords:
Internet of Things, Internet of Medical Things, Healthcare, Machine Learning, Blockchain, Artificial Intelligence, Deep Learning, Point of CareAbstract
The "Internet of Things" (IoT) is the infrastructure of web-connected devices that automatically gather and transport data through a remote network. Due to the rapid growth of IoT-based gadgets and their expansion towards making medical care facilities financially smart, proactive, and customizable, the "Internet of Medical Things (IoMT)" is presumed proactive in all areas of healthcare. Using cutting-edge technology, the IoMT-based healthcare system offers rapid and reliable treatment, increased communication, lower costs, and more. Machine learning has helped exploit various healthcare systems; fog computing reduces communication costs and latency; and block chain improves data security. Using cutting-edge techniques, this study detailed IoMT-based healthcare systems. This study discusses IoMT healthcare system methodologies and solutions in the context of modern technology, as well as future trends and applications, to better comprehend how IoMT can enhance healthcare now and in the future. Computer science-based AI algorithms and programs offer computers intelligence and efficiency in human-dominated fields. Machine learning (ML), deep learning (DL), classic neural networks, fuzzy logic, and speech recognition, each with their unique skills and features, can help modern medical science. Smart technologies simplify medical imaging, diagnosis, and decision-making. The Internet of Medical Things (IoMT) connects networked biomedical devices with software to improve human health. This review discusses IoMT and Point of Care (POC) devices used in cutting-edge healthcare fields such as heart assessment, cancer diagnosis, and diabetes management. AI assists cutting-edge biomedical robotic surgery. This review analyses how AI improves IoMT devices' functioning, detection accuracy, decision-making, and risk assessment. This overview covers the scientific and engineering challenges and prospects for AI-based cloud-integrated individualized IoMT devices for efficient POC biomedical system design for next-generation intelligent healthcare.
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