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: 31 December 2024 | Viewed by 3572

Special Issue Editors

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
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
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

Published Papers (3 papers)

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Research

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 584
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
Viewed by 1675
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 666
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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