Intelligent Computing and System Integration

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 February 2026 | Viewed by 778

Special Issue Editors


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Guest Editor
Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Interests: medical image processing; pattern recognition; intelligent computing; system integration

E-Mail Website
Guest Editor
Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Interests: industrial network; system integration; cloud computing; image processing; humanoid robot applications; internet of vehicles

E-Mail Website
Guest Editor
Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Interests: application of artificial intelligence; application of generative AI; medical image processing; multiobject tracking

Special Issue Information

Dear Colleagues,

This Special Issue pertains to the 7th International Symposium on Computer, Consumer and Control (IS3C2025) to be held in Taichung, Taiwan, 27–30 June, 2025. This conference offers a great opportunity for scientists, engineers, and practitioners to present the latest research results, ideas, developments, and applications. IS3C, held every two years, is hosted and sponsored by National Chin-Yi University of Technology, Taichung, Taiwan. As suggested by the name of the conference, the themes of this conference cover computer, multimedia and intelligence, communication application, integrated circuits, consumer electronics, renewable energy, systems and control, as well as digital signal processing. Original high-quality papers related to these themes are especially solicited, including theories, methodologies, and applications in computing, consumer, and control.

The rapid development of intelligent computing has significantly impacted various fields, enabling advanced system integration techniques that were previously unattainable. Intelligent computing leverages state-of-the-art methods such as artificial intelligence, machine learning, and neural networks to solve complex problems in system design, optimization, and integration. This Special Issue aims to explore the latest advancements in intelligent computing and their applications in integrating diverse systems across domains such as healthcare, automation, communication, and robotics.

This Special Issue welcomes theoretical and practical contributions focusing on innovative algorithms, models, and frameworks that enhance intelligent computing and system integration. We are particularly interested in research that addresses challenges in scalability, real-time performance, and reliability in integrated systems. Topics of interest include, but are not limited to, the following:

  • Advanced artificial intelligence methods for system integration.
  • Machine learning algorithms for real-time decision-making.
  • Optimization techniques in multi-system coordination.
  • Applications of intelligent computing in healthcare, smart cities, eco-driving, and industrial automation.
  • Interdisciplinary approaches to bridging computing and physical systems.

We also encourage submissions that demonstrate the integration of intelligent computing with emerging technologies, such as the Internet of Things (IoT), edge computing, Internet of Vehicles (IoV), computer vision, pattern recognition, and cyber-physical systems. Researchers and practitioners from academia and industry are invited to contribute original work or comprehensive reviews addressing the theoretical foundations and practical applications of intelligent computing and system integration.

We look forward to receiving your valuable contributions to this Special Issue, which aims to advance the field and inspire future research directions.

Prof. Dr. Sheng-Chih Yang
Prof. Dr. Chi-Chun Chen
Dr. Chuan-Wang Chang
Guest Editors

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Keywords

  • intelligent computing
  • system integration
  • artificial intelligence
  • optimization algorithms
  • internet of things
  • edge computing
  • data fusion
  • automation and control
  • interdisciplinary system design
  • healthcare applications
  • robotics
  • autonomous systems

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Published Papers (1 paper)

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Research

22 pages, 5825 KB  
Article
Development of a Smart Energy-Saving Driving Assistance System Integrating OBD-II, YOLOv11, and Generative AI
by Meng-Hua Yen, You-Xuan Lin, Kai-Po Huang and Chi-Chun Chen
Electronics 2025, 14(17), 3435; https://doi.org/10.3390/electronics14173435 - 28 Aug 2025
Viewed by 404
Abstract
In recent years, generative AI and autonomous driving have been highly popular topics. Additionally, with the increasing global emphasis on carbon emissions and carbon trading, integrating autonomous driving technologies that can instantly perceive environ-mental changes with vehicle-based generative AI would enable vehicles to [...] Read more.
In recent years, generative AI and autonomous driving have been highly popular topics. Additionally, with the increasing global emphasis on carbon emissions and carbon trading, integrating autonomous driving technologies that can instantly perceive environ-mental changes with vehicle-based generative AI would enable vehicles to better under-stand their surroundings and provide drivers with recommendations for more energy-efficient and comfortable driving. This study employed You Only Look Once version11 (YOLOv11) for visual detection of the driving environment, integrating it with vehicle speed data received from the OBD-II system. All information is integrated and processed using the embedded Nvidia Jetson AGX Orin platform. For visual detection validation, part of the test set includes standard Taiwanese road signs. Experimental results show that incorporating Squeeze-and-Excitation Attention (SEAttention), into YOLOv11 improves the mAP50–95 accuracy by 10.1 percentage points. Generative AI processed this information in real time and provided the driver with appropriate driving recommendations, such as gently braking, detecting a pedestrian ahead, or warning of excessive speed. These recommendations are delivered through voice output to prevent driver distraction caused by looking at an interface. When a red light or pedestrian is detected, early deceleration is suggested, effectively reducing fuel consumption while also enhancing driving comfort, ultimately achieving the goal of energy-efficient driving. Full article
(This article belongs to the Special Issue Intelligent Computing and System Integration)
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