Cloud Computing and the Internet of Medical Things for Health Data Analysis, Management, and Security: Challenges, Solutions, and Emerging Approaches

With the advancement of modern digital technologies, the convergence of cloud computing and the Internet of Medical Things (IoMT) has emerged as a transformative approach in digital healthcare systems. Cloud computing, through scalable, flexible, and service-oriented models (IaaS, PaaS, and SaaS), enables efficient and cost-effective storage, processing, and analysis of large-scale medical data. Concurrently, IOMT, by integrating wearable devices, biosensors, and implantable medical equipment in real time, provides an intelligent infrastructure for continuous clinical data collection. The synergy between these two technologies paves the way for services such as telemedicine, real-time patient monitoring, integrated management of electronic health records (EHRs), and predictive clinical data analytics. This paper explores the architectures, benefits, and challenges of this convergence, investigating security threats (e.g., Man-in-the-Middle attacks, privacy breaches, insider threats) and operational issues (e.g., big data management, processing latency, energy consumption in IOMT). It introduces advanced solutions such as hybrid Cloud-Fog-Edge architectures, lightweight encryption, Zero Trust security models, and the adoption of distributed machine learning. Furthermore, it analyzes future directions involving quantum computing, blockchain technology, and fifth/sixth generation networks (۵G/۶G) to enhance the performance, security, and scalability of digital healthcare systems. The findings indicate that realizing fully intelligent healthcare requires the development of integrated, secure ecosystems built upon global standards.

کلیدواژه ها:

Cloud Computing ، Internet of Medical Things (IoMT) ، Digital Health ، Medical Data Security ، Edge and Fog Computing ، Distributed Machine Learning