Intelligent software engineering for the medical Internet of Things: The role of fog and edge computing in energy optimization and latency reduction

tahereh hashemi¹ vahid khatibi bardsiri² seyyed hamid ghafori³

IOI Code : AAHD-ABCGKE
Publication : National Conference on Information Technology, Nanotechnology, Artificial Intelligence and Technological Futures Studies(itnaf.ir)
Abstract :
    The Internet of Medical Things (IoMT) faces challenges such as high latency, high energy consumption, and security threats. This systematic review based on the PRISMA protocol examines the role of fog and edge computing in overcoming these challenges. Analyzing 40 articles from reputable databases (2019-2025), the findings show that integrating these architectures with technologies such as deep reinforcement learning (DRL), artificial intelligence (AI), and spiking neural networks (SNN) leads to 30-70% latency reduction, 25-53% energy consumption, and security accuracy of more than 98%. However, challenges such as insufficient scalability and high resource consumption in AI models are prominent. This study emphasizes the need to integrate next-generation technologies such as blockchain and 6G, along with field trials, for practical deployment of IoMT.

Keywords : internet of medical things (iomt) fog computing edge computing energy optimization latency reduction cybersecurity deep reinforcement learning (drl)