Sensor-Enhanced Machine Learning for Complex System Optimization
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: 20 December 2026 | Viewed by 937
Special Issue Editor
Interests: internet of things; computer networks; sensor networks; wireless communication; edge computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid expansion of intelligent sensing technologies and machine learning (ML) is revolutionizing the design and optimization of complex systems across industries. As real-world systems grow in complexity, such as autonomous vehicles, energy infrastructures, smart factories, and medical devices, integrating real-time sensor data with machine learning (ML) models becomes essential for robust performance, adaptive control, and predictive maintenance.
This Special Issue aims to showcase the latest advances in sensor-enhanced machine learning (ML) techniques applied to the optimization of complex systems. We welcome original research, review articles, and case studies that explore novel algorithms, architectures, and applications at the intersection of sensor networks, edge computing, machine learning, and system control/optimization. The issue encourages interdisciplinary contributions bridging telecommunications, mechanical engineering, artificial intelligence, and cyber–physical systems.
Dr. Hossein Fotouhi
Guest Editor
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Keywords
- complex system
- optimization system
- control/optimization
- machine learning
- reinforcement learning
- cyber–physical systems
- Internet of Things
- digital twin
- smart sensors
- sensor networks
- edge computing
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