Engineering Applications of Artificial Intelligence for Sensors
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 19171
Special Issue Editors
Interests: artificial intelligence; machine learning; deep learning; applications of AI for sensors
Interests: artificial intelligence; machine learning; deep learning; applications; applications of AI for sensors
Special Issue Information
Dear Colleagues,
Artificial Intelligence (AI) is currently one of the most developing techniques in the engineering world and plays an important role worldwide. Thanks to the continuous development of machine learning, deep learning, etc. we constantly observe new applications of these techniques. Artificial intelligence techniques are widely used by engineers to solve a whole range of previously unseen problems.
Artificial intelligence methods require a lot of data, which we often obtain from many types of sensors and sensory technology. The combination of these two areas: data obtained from sensors and artificial intelligence algorithms, creates an extremely interesting, future-proof and promising interdisciplinary research area.
The Special Issue of "Engineering Applications of Artificial Intelligence for Sensors" provides an international space for the publication of papers describing the practical application of AI methods such us machine learning and deep learning in all aspects of engineering for sensors. Artificial intelligence techniques implemented in both open and closed code are acceptable. Artificial intelligence solutions based on cloud computing are particularly expected. This Special Issue aims to report innovative algorithms and applications of Artificial intelligence, machine learning, and deep learning to achieve improvement of life. Submitted articles should show interesting applications of artificial intelligence in engineering world where data for AI derives from sensors.
Potential topics include, but are not limited to:
- Machine learning application
- Deep learning applications
- Internet of things (IoT) and cyber-physical systems
- Intelligent transportation systems & smart vehicles
- Big data analytics, understanding complex networks
- Neural networks, fuzzy systems, neuro-fuzzy systems
- Deep learning and real-world applications
- Self-organizing, emerging or bio-inspired system
- Global optimization, Meta-heuristics and their applications: Evolutionary Algorithms, swarm intelligence, nature and biologically inspired meta-heuristics, etc.
- Architectures, algorithms and techniques for distributed AI systems, including multi-agent-based control and holonic control
- Decision-support systems
- Real-time intelligent automation, and their associated supporting methodologies and techniques, including control theory and industrial informatics
- Knowledge processing, knowledge elicitation and acquisition, knowledge representation, knowledge compaction, knowledge bases, expert systems
- Perception, e.g., image processing, pattern recognition, vision systems, tactile systems, speech recognition and synthesis
- Aspects of software engineering, e.g., intelligent programming environments, verification and validation of AI-based software, software and hardware architectures for the real-time use of AI techniques, safety and reliability
- Intelligent fault detection, fault analysis, diagnostics and monitoring
- Industrial experiences in the application of the above techniques, e.g., case studies or benchmarking exercises
- Robotics
Prof. Dr. Jarosław Kurek
Prof. Dr. Bartosz Świderski
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- machine learning
- deep learning
- simulation
- applications of AI for sensors
- neural network
- decision-support systems
- sensors
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