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Electronics
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New Insights Into Smart and Intelligent Sensors
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New Insights Into Smart and Intelligent Sensors

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Circuit and Signal Processing".

Deadline for manuscript submissions: 15 June 2025 | Viewed by 9229

Special Issue Editors

Dr. Ioan Burda

E-Mail Website
Guest Editor
Physics Department, Babes-Bolyai University, 400084 Cluj-Napoca, Romania
Interests: acoustic sensors; FPGA-based virtual instruments; front-end electronics for acoustic transducers; nonlinear circuits and intelligent systems; phase noise measurement; piezoelectric energy harvesting; smart materials
Special Issues, Collections and Topics in MDPI journals
Dr. Ajit Jha

E-Mail Website
Guest Editor
Department of Engineering Sciences, University of Agder, Jon Lilletuns vei 9, 4879 Grimstad, Norway
Interests: sensors; sensor fusion; image/signal processing; ML; ADAS functionalities towards autonomous systems; IoT
Special Issues, Collections and Topics in MDPI journals
Dr. Carlos Cruz

E-Mail Website
Guest Editor
Department of Electronics, University of Alcala, 28871 Madrid, Spain
Interests: sensors; detectors characterization; digital embedded systems; electronic design; data analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Smart sensor technologies have been deployed for monitoring and control mechanisms in a wide variety of environments (e.g., smart grids, flood and water level monitoring systems, environmental monitoring, traffic monitoring and control, energy saving, remote system monitoring, industrial applications, agriculture, etc.). Smart sensors provide information on a physical environment by using embedded microprocessors and wireless communication to monitor, examine, and maintain various systems. Computational resources are an integral part of the physical design of the sensor, without being reduced to a simple task of sending data for remote processing. Significant advances in miniaturization and increased computing power allow the implementation of learning algorithms that provide high data availability, leading to intelligent and autonomous sensors with distributed sensing capabilities. Technological developments in digital signal processing are driving major changes in the sensor domain. Thus, data fusion techniques and artificial intelligence concepts are now commonly used for better exploitation of sensor data as well as for successful integration into smart sensing applications. Innovative solutions to remedy some of the drawbacks of intelligent and smart sensors (hacking, additional maintenance costs, complex recalibration procedures, IT expertise required in operation, additional energy consumption, and the management of large volumes of data) are also encouraged. The purpose of this Special Issue is to explore advanced and visionary solutions related to intelligent and smart sensors.

Academic researchers, developers, and industry practitioners are welcome to submit original research contributions dealing with intelligent and smart sensors. Additionally, application-oriented and review papers are encouraged.

Dr. Ioan Burda
Dr. Ajit Jha
Dr. Carlos Cruz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Electronics 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 2400 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 flow sensor and pressure sensor
  • intelligent and smart tactile sensor or intelligent physiological sensor
  • intelligent velocity sensor, acceleration sensor, and force sensor
  • intelligent position sensor, attitude sensor, and displacement sensor
  • intelligent temperature sensor and dew-point sensors
  • intelligent light sensor, image sensor, or smart visual sensor
  • intelligent acoustic sensor and resonator sensor
  • intelligent digital sensor, smart adaptive sensor, and an IoT-based sensor
  • readout electronics and data acquisition systems for a smart sensor
  • digital signal processing deployment for a smart sensor
  • artificial intelligence for classification or forecasting purposes by an intelligent sensor

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Published Papers (6 papers)

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Research

19 pages, 21798 KiB  
Article
Advancing Sustainable Mobility: A Data Acquisition System for Light Vehicles and Active Mobility
by Matteo Verzeroli, Luigi Gaioni, Andrea Galliani, Luca Ghislotti, Paolo Lazzaroni and Valerio Re
Electronics 2024, 13(21), 4249; https://doi.org/10.3390/electronics13214249 - 30 Oct 2024
Viewed by 672
Abstract
Active mobility and light vehicles, such as e-bikes, are gaining increasing attention as sustainable transportation alternatives to internal combustion solutions. In this context, collecting comprehensive data on environmental conditions, vehicle performance, and user interaction is crucial for improving system efficiency and user experience. [...] Read more.
Active mobility and light vehicles, such as e-bikes, are gaining increasing attention as sustainable transportation alternatives to internal combustion solutions. In this context, collecting comprehensive data on environmental conditions, vehicle performance, and user interaction is crucial for improving system efficiency and user experience. This paper presents a data acquisition system designed to collect data from multiple sensor platforms. The architecture is optimized to maintain low power consumption and operate within limited computational resources, making it suitable for real-time data acquisition on light vehicles. To achieve this, a data acquisition module was developed using a single-board computer integrated with a custom shield, which also captures data related to the assistance of an e-bike motor through a wireless interface. The paper provides an in-depth discussion of the architecture and software development, along with a detailed overview of the sensors used. A demonstrator was created to verify the system architecture idea and prove the potentialities of the system overall. The demonstrator has been qualified by professional and semi-professional riders in the framework of the Giro-E, a cyclist event which took place in May 2024, on the same roads of the Giro d’Italia. Finally, some preliminary analyses on the data acquired are provided to show the performance of the system, particularly in reconstructing the user behavior, the environmental parameters, and the type of road. Full article
(This article belongs to the Special Issue New Insights Into Smart and Intelligent Sensors)
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26 pages, 1178 KiB  
Article
A Taxonomy of Low-Power Techniques in Wearable Medical Devices for Healthcare Applications
by Workineh Tesema, Worku Jimma, Muhammad Iqbal Khan, Johan Stiens and Bruno da Silva
Electronics 2024, 13(15), 3097; https://doi.org/10.3390/electronics13153097 - 5 Aug 2024
Cited by 1 | Viewed by 1528
Abstract
Chronic diseases are the most prevalent and non-communicable health crisis globally. Most chronic disease patients require continuous physiological monitoring, using wearable technology for timely treatment, precise illness detection, and preventive healthcare. Nonetheless, efficient power management is required for such resource-constrained wearable devices. This [...] Read more.
Chronic diseases are the most prevalent and non-communicable health crisis globally. Most chronic disease patients require continuous physiological monitoring, using wearable technology for timely treatment, precise illness detection, and preventive healthcare. Nonetheless, efficient power management is required for such resource-constrained wearable devices. This work aims to analyze low-power techniques (LPTs) in wearable medical devices using a data-driven approach and identify novel approaches promising higher power savings. Through an intensive literature analysis, we identify the most relevant LPTs for minimizing power consumption in wearable devices for physiological monitoring while recognizing the barriers to adopting these techniques. As a result, a novel taxonomy based on the common characteristics of the LPTs is proposed, along with strategies for the combination of LPTs. Through our analysis, we propose possible enhancements in using LPTs and suggest mechanisms for the medical device industry to facilitate their adoption. Overall, our proposed strategies guide the use of LPTs on wearable medical devices toward continuous physiological monitoring. Full article
(This article belongs to the Special Issue New Insights Into Smart and Intelligent Sensors)
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20 pages, 14884 KiB  
Article
Current Sensor Fault-Tolerant Control Strategy for Speed-Sensorless Control of Induction Motors Based on Sequential Probability Ratio Test
by Feige Zhang, Shesheng Gao, Wenjuan Zhang, Guo Li and Chao Zhang
Electronics 2024, 13(13), 2476; https://doi.org/10.3390/electronics13132476 - 25 Jun 2024
Viewed by 875
Abstract
In the speed-sensorless vector control of induction motors (IMs), the speed estimation accuracy suffers from the deteriorated current measurement caused by the current sensor faults, such as open circuit in one phase, DC bias, and odd harmonics. In this paper, a novel speed [...] Read more.
In the speed-sensorless vector control of induction motors (IMs), the speed estimation accuracy suffers from the deteriorated current measurement caused by the current sensor faults, such as open circuit in one phase, DC bias, and odd harmonics. In this paper, a novel speed estimation strategy based on the current sensor fault-tolerant control is proposed to improve the speed estimation accuracy under the current sensor faults. First, to detect the current sensor faults in real time, the sequential probability ratio test is introduced to the system by using the innovations of the extended Kalman filter (EKF). Second, to ensure speed estimation accuracy, a double-cascading second-order generalized integrator (DSOGI) is employed to reconstruct the faulty current information when a fault is identified. Finally, the reconstructed current information is fed back to the sequential probability extended Kalman filter (SPEKF), which estimates the rotor speed of the IM, and high-accuracy speed estimation under the condition of current sensor faults is achieved. The effectiveness of the proposed strategy is validated by a series of experiments, which were conducted on a 3 kW induction motor drive platform. Full article
(This article belongs to the Special Issue New Insights Into Smart and Intelligent Sensors)
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17 pages, 4886 KiB  
Article
Comparison of Neck Pain and Posture with Spine Angle Tracking System between Static and Dynamic Computer Monitor Use
by Hayoung Kim, Young Il Won, Soohee Kang, Yunhee Choi, Jin Ho Park, Jongshill Lee, In Young Kim and Chun Kee Chung
Electronics 2024, 13(7), 1363; https://doi.org/10.3390/electronics13071363 - 4 Apr 2024
Viewed by 1326
Abstract
This study investigates the effect of dynamic changes in monitor height and tilt on neck pain and posture of computer users. Using a wearable device, we aim to compare neck pain and spine angle between static and dynamic monitors. A spine angle tracking [...] Read more.
This study investigates the effect of dynamic changes in monitor height and tilt on neck pain and posture of computer users. Using a wearable device, we aim to compare neck pain and spine angle between static and dynamic monitors. A spine angle tracking system using the Inertial Measurement Unit (IMU) was proposed, and the accuracy was validated. Eight office workers participated for five hours over two days, and each day used either a static monitor or a dynamic monitor that changed height and tilt every 30 min. The angles of C0, C7, L1, and S1 endplates were estimated using the proposed system. Changes in neck pain and spine angle with time were compared in static and dynamic monitors. The intraclass correlation coefficient confirmed a high concordance between the estimated and actual angles (p < 0.001). Rehabilitation Bioengineering Group (RBG) score increased less in the dynamic monitor compared to the static monitor (p = 0.003). Spinal curvatures are bent in the static monitor compared to the dynamic monitor. The estimated angles aligned well with X-ray measurements. A dynamic monitor that changes height and tilt at regular intervals may reduce neck pain increase and reduce bend forward posture compared to a static monitor. Full article
(This article belongs to the Special Issue New Insights Into Smart and Intelligent Sensors)
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33 pages, 19008 KiB  
Article
A Fully Programmable DAQ Board of Vibrational Signals from IEPE Sensors: Hardware and Software Design, Performance Analysis
by Roberto De Fazio, Lorenzo Spongano, Arcangelo Messina and Paolo Visconti
Electronics 2024, 13(7), 1187; https://doi.org/10.3390/electronics13071187 - 24 Mar 2024
Cited by 3 | Viewed by 2443
Abstract
Vibration analysis is commonly used to assess machinery conditions, earthquake detection, and structural monitoring. Commercially available DAQs (Data Acquisition Systems) feature high costs and limited versatility in terms of end-user hardware/firmware customization, making it difficult to adapt them to the input signal features [...] Read more.
Vibration analysis is commonly used to assess machinery conditions, earthquake detection, and structural monitoring. Commercially available DAQs (Data Acquisition Systems) feature high costs and limited versatility in terms of end-user hardware/firmware customization, making it difficult to adapt them to the input signal features and add supplementary functionalities. Hence, this research aims to develop a custom acquisition board for detecting vibration signals via IEPE (Integrated Electronic Piezoelectric) sensors, considering the limitations of commercially available systems, and building upon solutions found in the literature. The DAQ board was intended for remote vibration monitoring of infrastructure and machinery for industrial applications, allowing the implementation of predictive maintenance strategies. The proposed DAQ board has two independent and fully configurable channels, which can be set for acquiring signals from IEPE sensors or generic voltage sources. The DAQ board relies on the STM32F401 microcontroller to manage the acquisition from high-speed ADCs, process data, and store them in mass memory (SD card). During acquisition, the DAQ implements a batch acquisition strategy based on a buffer flash memory for temporarily storing ADCs data, which are iteratively poured into mass memory. Also, the board has Bluetooth connectivity to transmit acquired data and receive commands remotely. A prototype of the DAQ board was developed and tested with several waveforms, including vibration signals. The tests showed that the board can acquire vibration signals and compute the FFT onboard. The DAQ demonstrated a good balance between performance, accuracy, flexibility, and cost, making it suitable for several industrial applications and allowing for scalability and integration potential. Full article
(This article belongs to the Special Issue New Insights Into Smart and Intelligent Sensors)
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15 pages, 4623 KiB  
Article
An Open-Source Face-Aware Capture System
by Md Abdul Baset Sarker, S. M. Safayet Hossain, Naveenkumar G. Venkataswamy, Stephanie Schuckers and Masudul H. Imtiaz
Electronics 2024, 13(7), 1178; https://doi.org/10.3390/electronics13071178 - 22 Mar 2024
Viewed by 1320
Abstract
Poor-quality facial images pose challenges in biometric authentication, especially in passport photo acquisition and recognition. This study proposes a novel and open-source solution to address these issues by introducing a real-time facial image quality analysis utilizing computer vision technology on a low-power single-board [...] Read more.
Poor-quality facial images pose challenges in biometric authentication, especially in passport photo acquisition and recognition. This study proposes a novel and open-source solution to address these issues by introducing a real-time facial image quality analysis utilizing computer vision technology on a low-power single-board computer. We present an open-source complete hardware solution that consists of a Jetson processor, a 16 MP autofocus RGB camera, a custom enclosure, and a touch sensor LCD for user interaction. To ensure the integrity and confidentiality of captured facial data, Advanced Encryption Standard (AES) is used for secure image storage. Using the pilot data collection, the system demonstrated its ability to capture high-quality images, achieving 98.98% accuracy in storing images of acceptable quality. This open-source, readily deployable, secure system offers promising potential for diverse real-time applications such as passport verification, security systems, etc. Full article
(This article belongs to the Special Issue New Insights Into Smart and Intelligent Sensors)
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