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AI Sensors and Transducers
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Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore
Prof. Dr. Toshihiro Itoh
Department of Precision Engineering, Graduate School of Engineering, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8654, Japan
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AI Sensors and Transducers

Abstract submission deadline
31 December 2025
Manuscript submission deadline
30 April 2026
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Topic Information

Dear Colleagues,

This Topic was created in collaboration with the 2nd International Conference on AI Sensors and Transducers (AIS 2025, https://sciforum.net/event/AIS2025), which will be held in Kuala Lumpur, Malaysia, from 29 July to 3 August 2025. Conference participants of AIS 2025 are cordially invited to contribute a full manuscript to this Topic and will receive a 20% discount on the Article Processing Charge.

In addition to the conference papers, we also welcome regular submissions. We are delighted to invite contributions at the forefront of sensors, sensing technology, artificial intelligence (AI) sensors and AI-enhanced sensing systems, as well as transducers and AI-enhanced transducers. This event promises to be an exciting platform for exploring cutting-edge advances and fostering collaboration in the rapidly evolving field of AI, sensors, and transducers.

Key areas of focus for this conference include, but are not limited to, the following:

  • Sensing Systems Enhanced by AI;
  • Computer Vision;
  • AI Sensors Based on Vision and Voice Data;
  • Data Fusion and Processing with Sensor Applications;
  • Sensor Modality/Sensing System Enhanced by Multi-Modality Deep Learning;
  • Data Mining for Sensor Applications;
  • Edge Computing Technologies;
  • Neuromorphic Computing;
  • Computing in Memory;
  • In Sensor Computing;
  • MEMS Sensors Enhanced by Edge Computing;
  • CMOS MEMS/NEMS and AI Sensors;
  • Hardware for Enabling Artificial Intelligence of Things (AIoT) Systems;
  • Heterogeneous Integration for AIoT Systems;
  • Chiplet and System-in-Package (SiP) for AIoT-on-a-Chip;
  • Autonomous AIoT Systems;
  • Cutting-Edge AI Sensor Technologies;
  • Generative AI Technologies;
  • Photonics AI Accelerator;
  • Innovative AI Sensor Applications Across Industries;
  • Physical Sensors and MEMS;
  • Chemical Sensors;
  • Medical Sensors;
  • Gas Sensors;
  • Ultrasound Sensors;
  • Optical Sensors, CMOS Image Sensors, and IR Focal Plane Array;
  • Magnetic Sensors and Spintronics;
  • Biosensors and Bioelectronics;
  • Wearable Sensors;
  • Implantable Sensors, Neural Interfaces, and Electroceuticals;
  • Sensors for Intelligent Robots;
  • Sensors for Drones;
  • Self-powered Sensors;
  • Zero-biased Sensors and Science;
  • Nanomaterials, Nanosensors, and NEMS;
  • Si Photonics (SiPh) for Sensing;
  • Nanophotonics and metalenses for Sensing;
  • Metasurface and Mid-IR Sensing;
  • Metamaterials and THz Sensing;
  • Spectroscopy and Sensing Technology;
  • Internet of Things (IoT) and Sensor Networks;
  • Energy Harvesting for IoT Sensors;
  • Remote Sensors, Data Acquisition, and Processing;
  • Integration of Actuators with Sensors for Smart System.

Dr. Chengkuo Lee
Prof. Dr. Toshihiro Itoh
Topic Editors

Keywords

  • sensors
  • AI
  • transducers
  • AI-enhanced sensing systems
  • MEMS

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
AI Sensors
aisens 		- - 2025 15.0 days * CHF 1000 Submit
Chemosensors
chemosensors 		3.7 7.3 2013 20.5 Days CHF 2000 Submit
Sensors
sensors 		3.5 8.2 2001 19.7 Days CHF 2600 Submit
Micromachines
micromachines 		3.0 6.0 2010 17.2 Days CHF 2100 Submit
Robotics
robotics 		3.3 7.7 2012 21.8 Days CHF 1800 Submit

* Median value for all MDPI journals in the first half of 2025.


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Published Papers (1 paper)

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23 pages, 2058 KB  
Article
Inductive Displacement Sensor Operating in an LC Oscillator System Under High Pressure Conditions—Basic Design Principles
by Janusz Nurkowski and Andrzej Nowakowski
Sensors 2025, 25(19), 6078; https://doi.org/10.3390/s25196078 - 2 Oct 2025
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Abstract
The paper presents some design principles of an inductive displacement transducer for measuring the displacement of rock specimens under high hydrostatic pressure. It consists of a single-layer, coreless solenoid mounted directly onto the specimen and connected to an LC oscillator located outside the [...] Read more.
The paper presents some design principles of an inductive displacement transducer for measuring the displacement of rock specimens under high hydrostatic pressure. It consists of a single-layer, coreless solenoid mounted directly onto the specimen and connected to an LC oscillator located outside the pressure chamber, in which it serves as the inductive component. The specimen’s deformation changes the coil’s length and inductance, thereby altering the oscillator’s resonant frequency. Paired with a reference coil, the system achieves strain resolution of ~100 nm at pressures exceeding 400 MPa. Sensor design challenges include both electrical parameters (inductance and resistance of the sensor, capacitance of the resonant circuit) and mechanical parameters (number and diameter of coil turns, their positional stability, wire diameter). The basic requirement is to achieve stable oscillations (i.e., a high Q-factor of the resonant circuit) while maintaining maximum sensor sensitivity. Miniaturization of the sensor and minimizing the tensile force at its mounting points on the specimen are also essential. Improvement of certain sensor parameters often leads to the degradation of others; therefore, the design requires a compromise depending on the specific measurement conditions. This article presents the mathematical interdependencies among key sensor parameters, facilitating optimized sensor design. Full article
(This article belongs to the Topic AI Sensors and Transducers)
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