AI-Driven Intelligent Systems in Energy, Healthcare, and Beyond

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 15 February 2026 | Viewed by 20

Special Issue Editors


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Guest Editor
Department of Electronic and Computer Engineering, Ritsumeikan University, Kusatsu 525-8577, Japan
Interests: processor architecture; high-performance computing; AI-based IoT; underwater drones; cultural heritage preservation and protection
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Guest Editor
Faculty of Information Engineering, Toyama Prefectural University, Imizu-shi 939-0398, Toyama, Japan
Interests: eartificial intelligence; image processing; embedded systems
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School of Automation and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China
Interests: artificial intelligence; high-performance computing; machine vision

Special Issue Information

Dear Colleagues,

Artificial intelligence (AI), in conjunction with the Internet of Things (IoT) and robotics, is advancing intelligent, autonomous, and data-centric solutions across various sectors. Notably, energy and healthcare have emerged as two of the most impactful application domains. In the energy domain, the convergence of AI and IoT is modernizing infrastructure, optimizing consumption, and supporting sustainability goals. Real-time data from smart grids and renewable sources, when combined with AI-driven analytics, enable predictive maintenance, intelligent control, and demand-side optimization, contributing to more resilient and efficient energy systems. In healthcare, AI and robotics are reshaping diagnostics, treatment, and patient care through applications such as AI-driven imaging, wearable monitoring, robot-assisted surgeries, and autonomous rehabilitation. Advances in signal and image processing are improving diagnostic accuracy and enabling personalized healthcare delivery. These advancements are further empowered by progress in high-performance AI systems, including model compression, parallel computing, and deployment on edge and embedded platforms. Lifelong learning and self-adaptive algorithms enhance the responsiveness and robustness of AI systems in dynamic environments. This Special Issue aims to bring together cutting-edge research at the intersection of AI, high-performance computing, and robotics, with a focus on real-world intelligent applications in energy, healthcare, and beyond.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • AI-enabled energy optimization, including intelligent demand response, load balancing, and consumption forecasting;
  • IoT-based monitoring and predictive maintenance for energy systems and related domains;
  • Secure and resilient AI- and IoT-enabled cyber–physical energy systems;
  • High-performance AI architectures, including model compression, parallelization, and deployment on heterogeneous hardware;
  • Edge and embedded AI for low-latency, energy-efficient intelligence in constrained environments;
  • AI-powered robotics for domain-specific applications such as healthcare and industrial automation;
  • Signal and image processing for diagnostics, monitoring, and rehabilitation.

Prof. Dr. Lin Meng
Dr. Xiangbo Kong
Dr. Hengyi Li
Guest Editors

Manuscript Submission Information

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Keywords

  • artificial intelligence (AI)
  • internet of things (IoT)
  • high-performance computing
  • edge computing
  • embedded systems
  • robotic systems
  • image processing
  • energy system
  • healthcare

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Published Papers

This special issue is now open for submission.
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