Guest Editors
Dr. Héctor Migallón
Email: hmigallon@umh.es
Affiliation: Computer Engineering Department,
Miguel Hernández University,
Elche, 03202,
SPAIN
Homepage:
Research Interests: high-performance computing (HPC), heterogeneous computing (GPU/CPU/Many-core), image and video processing, metaheuristic optimization, industry 4.0/5.0 applications, advanced imaging and sensor data analysis
Dr. Miguel Martínez-Rach
Email: mmrach@umh.es
Affiliation: Computer Engineering Department,
Miguel Hernández University,
Elche, 03202,
SPAIN
Homepage:
Research Interests: image and video processing, multimedia systems, quality assessment and perceptual video metrics, industry 4.0/5.0 applications, advanced imaging and sensor data analysis
Dr. Otoniel López-Granado
Email: otoniel@umh.es
Affiliation: Computer Engineering Department,
Miguel Hernández University,
Elche, 03202,
SPAIN
Homepage:
Research Interests: image and video processing, real-time multimedia processing, vehicular networks and video streaming, artificial intelligence, machine learning and data-driven methods
Summary
The convergence of computational intelligence and high-performance techniques is redefining next-generation industrial systems and sensing applications.
As sensing technologies evolve toward higher resolution and multimodal data acquisition, advanced computational methods become essential to process, analyze, and interpret this complex information in real time.
Advanced industrial systems are undergoing a profound transformation driven by the integration of computational intelligence, high-performance computing, and next-generation sensing technologies. These systems increasingly rely on large-scale, heterogeneous, and multimodal data produced by spectral, thermal, visual, and IoT-based sensors, requiring efficient architectures and algorithms capable of processing and interpreting information in real time.
Computational intelligence methods, such as intelligent optimization, ML models and AI models, enable industrial processes to become more autonomous, precise, and adaptive. At the same time, high-performance and heterogeneous computing platforms are essential to sustain the growing computational demands of modern industrial environments. This Special Issue focuses on methodologies, tools, and applications that advance intelligent, scalable, and efficient industrial systems, addressing challenges in algorithmic design, data processing, sensing integration, and real-time performance.
Suggested themes:
· AI and machine learning methods for industrial automation and optimization
· Parallel, GPU-accelerated, and heterogeneous computing techniques for industrial workloads
· Advanced signal, image, and multimodal sensor data processing
· Design and integration of advanced sensing systems in industrial environments
· Real-time computational frameworks and applications in industrial environments
Keywords
Computational intelligence; Hyperspectral and thermal imaging; Advanced sensing systems; High-performance computing; Multimodal sensor data processing; Intelligent industrial systems; Real-time industrial systems
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