Artificial Intelligence for Smart Mobility and Industrial Automation
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".
Deadline for manuscript submissions: 15 December 2026 | Viewed by 274
Editors
Interests: autonomous robotics; artificial intelligence in industry; computer vision
Special Issues, Collections and Topics in MDPI journals
Interests: automatic control; adaptive control; robust control; non-linear control; LPV systems; robot control; dynamic system modeling; simulation of dynamic systems; industrial robotics; mobile robotics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) is rapidly transforming transportation systems and industrial environments, enabling a new generation of intelligent, autonomous, and highly efficient infrastructures. Advances in machine learning, deep learning, and data-driven control are facilitating the development of smart mobility solutions and next-generation industrial automation systems capable of operating in complex and dynamic scenarios.
In smart mobility, AI technologies support the deployment of autonomous and connected vehicles, intelligent transportation systems, and real-time traffic management platforms. These solutions leverage large-scale data analytics, sensor fusion, and advanced perception algorithms to improve safety, efficiency, and sustainability in modern mobility ecosystems.
At the same time, industrial automation is evolving through the integration of AI with cyber–physical systems, robotics, and Industrial Internet of Things (IIoT) platforms. Concepts such as digital twins, predictive maintenance, edge intelligence, and adaptive control are enabling smarter manufacturing processes and more resilient industrial infrastructures.
This Special Issue aims to bring together recent advances in AI methodologies and applications for smart mobility and industrial automation, highlighting innovative solutions that improve efficiency, reliability, and sustainability in intelligent transportation and industrial systems.
Prof. Dr. Antoni Grau
Dr. Yolanda Bolea
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- machine learning
- deep learning
- smart mobility
- intelligent transportation systems
- autonomous vehicles
- industry 4.0
- industrial automation
- robotics
- edge AI
- industrial internet of things (IIoT)
- digital twins
- predictive maintenance
- cyber–physical systems
- smart manufacturing
- sensor fusion
- computer vision
- data-driven control
- reinforcement learning
- intelligent infrastructure
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