Advanced Electromagnetic Sensors Technologies and Their Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Electronic Sensors".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 343
Editors
Interests: numerical computation of electromagnetic fields; inverse problems in low-frequency electromagnetism; thermonuclear fusion; superconducting magnets; artificial intelligence for electromagnetism
Special Issues, Collections and Topics in MDPI journals
Interests: numerical modeling and computation of electromagnetic fields in electrical and biomedical engineering; inverse methods in low-frequency electromagnetics; non-destructive material evaluation; engineered metamaterials; electromagnetic interactions with biomedical implants
Interests: electromagnetic fields computation and lightning modeling; HVDC electrodes design
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue is devoted to recent advances in electromagnetic sensors and sensing technology, both for direct and indirect measurements. Electromagnetic sensing technologies are central to a wide spectrum of applications, including non-destructive testing (NDT) and evaluation of materials and structures, biomedical diagnostics and monitoring, geophysical exploration and subsurface characterization, and remote or contactless measurement of electrical currents and sources. Across these domains, the common scientific challenge lies in extracting reliable and physically meaningful information from possibly indirect, noisy, and often incomplete measurements. This challenge naturally leads to demanding sensing technologies able to suitably reduce errors and uncertainties. In addition, recent progress in theory, computation, and data-driven methods have significantly expanded the range of solvable electromagnetic inverse problems. In this way, artificial intelligence plays a growing role both in the design of innovative sensors and in the treatment of data.
We are therefore pleased to invite relevant contributions to this Special Issue of Sensors.
The primary aim of this Special Issue is to highlight emerging methodologies that go beyond classical measurement and data inversion paradigms, with a strong focus on application-driven advances in NDT, biomedical sensing, geophysics, and remote current measurement. We particularly encourage submissions that integrate physics-based electromagnetic models with data-driven techniques, including machine learning, deep learning, and hybrid physics–AI frameworks. Topics of interest include new measurement principles, sensor design, learning-enhanced inverse problems strategies, uncertainty quantification, and neural-network-based approaches for imaging, classification, and parameter estimation.
Contributions addressing the interpretability, generalization, and robustness of AI-based methods for measurement treatment are especially welcome, as these aspects are crucial for safety-critical and high-reliability applications such as medical diagnostics, infrastructure inspection, and geophysical monitoring. Novel sensing architectures, multi-modal and multi-physics approaches, and experimental validations that demonstrate improved inversion performance are also within the scope of this collection.
Submissions should clearly describe the targeted application, the underlying electromagnetic model, and the associated data handling procedures. Methodological, technological and application-driven papers are welcome, provided they clearly demonstrate how new sensing technologies or inversion strategies advance the state of the art in electromagnetic sensing.
Through this Special Issue, we aim to provide a coherent snapshot of current research directions and to stimulate cross-fertilization between research in electromagnetic sensing, inverse problems, and artificial intelligence.
Prof. Dr. Alessandro Formisano
Dr. Bojana Petkovic
Dr. Daniele Mestriner
Guest Editors
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- electromagnetic sensing
- inductive sensors
- hall sensors
- magnetostrictive sensors
- signal conditioning circuitry
- data-driven measurement techniques
- non-destructive testing (NDT)
- biomedical electromagnetic imaging
- geophysical electromagnetics
- remote current measurement
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