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Recent Trends in AI-Based Intelligent Sensing Systems and IoTs

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 451

Special Issue Editors


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Department of Electronic Engineering, College of Physical Science and Technology, Central China Normal University, Wuhan 430079, China
Interests: intelligent information processing and control theory; wireless sensor network technology and embedded product development
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Instrument and Electrical Department, School of Aerospace Engineering, Xiamen University, Xiamen 361102, China
Interests: instrument science and technology; NDT&E; X-ray detection; spectroscopy

Special Issue Information

Dear Colleagues,

Sensors play a vital role in our daily lives and are an essential component for Internet of Things (IoT)-based systems as they can collect data and help the IoT make smart and intelligent decisions. Due to its autonomous decision-making ability to solve complex problems, AI-based intelligent sensing has gained significant attention.

Today, smart sensors complement and enhance the capabilities of human beings and have been widely embraced in numerous application areas. Artificial intelligence (AI) has gained astounding growth in the domains of natural language processing, machine learning (ML), and computer vision. Moreover, AI-based sensors will empower the next generation of IoT applications.

This Special Issue focuses on the integration of cutting-edge sensor systems, artificial intelligence (AI), and Internet of Things (IoT) technologies. Research areas may include (but are not limited to) the following:

  • Smart sensors;
  • IoT applications;
  • Machine learning and AI;
  • Wireless sensor networks;
  • Human–computer interaction;
  • Intelligent information systems;
  • Intelligent decision support systems;
  • Industry 4.0 and advanced manufacturing;
  • Motor sensor and control;
  • AI-based algorithms for sensor data mining;
  • AI-based algorithms for real-time communications.

Prof. Dr. Shaocheng Qu
Prof. Dr. Zheng Fang
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

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

  • intelligent sensing
  • Internet of Things
  • artificial intelligence

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Published Papers (1 paper)

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Research

22 pages, 6945 KiB  
Article
Parameter Calculation and Rotor Structure Optimization Design of Solid Rotor Induction Motors
by Hao Xu, Jinghong Zhao and Sinian Yan
Sensors 2025, 25(9), 2929; https://doi.org/10.3390/s25092929 - 6 May 2025
Viewed by 221
Abstract
Solid rotor induction motors have a solid body rotor, which leads to low efficiency and power factor, and currently, the rotor is mostly optimized by slotted and squirrel cage structures. A generalized multilayer analytical model for different rotor structures is established, which can [...] Read more.
Solid rotor induction motors have a solid body rotor, which leads to low efficiency and power factor, and currently, the rotor is mostly optimized by slotted and squirrel cage structures. A generalized multilayer analytical model for different rotor structures is established, which can consider the effects of rotor eddy currents and saturation, based on which a generalized equivalent circuit model is established. The effects of number of slots, depth of slots, width of slots, squirrel cage material and end ring thickness on rotor impedance, torque and rotor losses are analyzed. On this basis, with efficiency, power factor, starting torque and starting current as the optimization objectives, and the number of slots, slot depth, slot width, squirrel cage material and end ring thickness as the optimization variables, the optimization schemes of slotted rotor and squirrel cage rotor are obtained by using the three-dimensional finite element method. The theoretical analysis is verified by finite element simulation and prototype experiment, and the results show that the electromagnetic parameters of solid rotor induction motors with different rotor structures can be accurately calculated using the universal magnetic field analytical model and the universal equivalent circuit model with an error within 5.8%. Slotted and squirrel cage rotors can effectively improve the motor power factor and efficiency, but this will lead to a decrease in starting performance. For the optimization function established in this paper, compared with the smooth rotor, the performance of the squirrel cage rotor is improved by 6.08%, which verifies the accuracy and validity of this paper and the optimization design scheme. Full article
(This article belongs to the Special Issue Recent Trends in AI-Based Intelligent Sensing Systems and IoTs)
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