Advanced Self-X Sensory Systems: Concepts, Challenges, and Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: 25 May 2025 | Viewed by 70
Special Issue Editor
Interests: integrated sensor systems related to microelectronics/MEMS and intelligent sensor systems related to computational intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The intriguing versatility, adaptability, robustness, resilience and restoration capabilities of living beings have always been the envy of engineers. However, technical solutions have been very far from that for a long time. Approaches based on mimicking neural networks and nervous systems are one interesting direction of study, a technically more universal and rewarding one is the creation of self-X or self-* systems, which provide in a more abstract embodiment, not confined to neurons and neural networks, numerous of the coveted capabilities of living beings. Self-X capabilities are among many more, e.g., self-monitoring, -calibration, -trimming, and -healing/repairing, which have been postulated as key functionalities for Industry 4.0 and numerous other deployment fields, e.g., IoT, CP(P)S, wearable electronics, AAL/healthcare assistance systems, point-of-care-systems, etc. The surging advance in micro/nano integration and packaging technologies, and the advent of a plethora of novel sensory concepts and technologies also opens the door to expend extra effort and system complexity required on all levels, both in the analog and/or the digital domain, for the realization of self-X functionality and related optimization and reconfiguration, and/or adaptation resources in the application systems. This explicitly extends design automation techniques from design time to run time, being able to deal with both static and dynamically occurring issues for system performance, which is denoted as extrinsic and intrinsic evolution or optimization in the related field of Evolvable Hardware Systems. Goals have to be addressed, such as the following: cost-effectiveness, long-term system reliability/dependability and accuracy, consistency of modeling, simulation and rapid design of heterogeneous systems, suitability of observer and/or non-obtrusive sensors in the optimization loop, information gain from redundant homogeneous imperfect sensors by dedicated dimensionality reducing mapping, and sensors with micro actuation or switching devices, for example.
Topics of primary interest for this Special Issue include, but are not limited to, the following: systems with multi-level and/or mixed-signal self-x- (or self-*) -capabilities, related redundancy and reconfiguration and/or adaptation concepts, architectures, and actuator/switching devices for sensors, inherently robust signal representations and processing, including time or pulse coding, homogeneous and/or heterogeneous multi-sensor approaches, design automation and CAD, yield optimization and reliability issues, and achieving high-quality and reliable references and reduced measurement uncertainty, e.g., NIST NoaC activity, artificial immune systems, multidimensional signal processing algorithms, dimensionality reduction techniques, learning and optimization methods, sensor fusion, and sensor, and data visualization.
In this Special Issue, we seek to collect review articles, original research papers, and short communications, as well as history surveys, covering aspects of multi-level self-X systems in the context of the given primary interest.
Authors are welcome to contact the Guest Editor prior to submission if their work addresses additional issues and challenges to clarify whether this falls within the general scope of this Special Issue.
Prof. Dr. Andreas König
Guest Editor
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Keywords
- self-x-capabilities
- reconfiguration and adaptation
- design automation
- yield and dependability optimization
- extrinsic and intrinsic evolution
- run-time optimization
- robust signal representations
- non-obtrusive sensors
- non-ideal observer compensation
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