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Selected Papers from IMETI 2022

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 3181

Special Issue Editors

Special Issue Information

Dear Colleagues,

The 11th International Multi-Conference on Engineering and Technology Innovation (IMETI 2022) will be held in Kaohsiung, Taiwan, 28 October–1 November 2022. It aims to bring together engineering technology expertise. Professionals from industry, academia, and the government with interests in the discourse on research and development, professional practice, and business, as well as those who manage science and engineering fields, are welcome to attend the event. IMETI2022 consists of four sub-conferences (ICATI 2022, ICBEI 2022, ICSI2022, and ICECEI 2022) and more than 30 regular and special sessions (http://imeti.org/IMETI2022/).

The main goal of this Special Issue, “Selected Papers from IMETI 2022”, is to present the latest advances in research and novel applications of sensor technologies and methods, sensor networks, materials for sensors, etc. Potential topics include, but are not limited to:

  • smart and intelligent sensors;
  • sensing principles and mechanisms;
  • chemical/gas sensors, mechanical/optical sensors, MEMS and nano-sensors, other sensors, etc.;
  • novel sensing technologies;
  • flexible and wearable sensors;
  • energy harvesting for autonomous sensors;
  • big data in sensing systems;
  • sensor data visualization;
  • sensor data fusion sensor networks and applications;
  • wireless network protocols;
  • wired and wireless sensor systems;
  • communication standards for WSN;
  • energy efficiency and energy harvesting;
  • power management;
  • ad hoc networks;
  • materials for sensors;
  • smart objects/smart cities/smart buildings and home monitoring;
  • environment monitoring;
  • industrial monitoring;
  • animal and object tracking.

Prof. Dr. Wen-Hsiang Hsieh
Prof. Dr. Minvydas Ragulskis
Prof. Dr. Jia-Shing Sheu
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. 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

  • sensor
  • WSN
  • IoT
  • IMETI
  • ICSI
  • ICATI

Published Papers (3 papers)

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Research

16 pages, 8867 KiB  
Article
Implantable pH Sensing System Using Vertically Stacked Silicon Nanowire Arrays and Body Channel Communication for Gastroesophageal Reflux Monitoring
by Changhee Kim, Seungju Han, Taehwan Kim and Sangmin Lee
Sensors 2024, 24(3), 861; https://doi.org/10.3390/s24030861 - 29 Jan 2024
Viewed by 665
Abstract
Silicon nanowires (SiNWs) are emerging as versatile components in the fabrication of sensors for implantable medical devices because of their exceptional electrical, optical, and mechanical properties. This paper presents a novel top-down fabrication method for vertically stacked SiNWs, eliminating the need for wet [...] Read more.
Silicon nanowires (SiNWs) are emerging as versatile components in the fabrication of sensors for implantable medical devices because of their exceptional electrical, optical, and mechanical properties. This paper presents a novel top-down fabrication method for vertically stacked SiNWs, eliminating the need for wet oxidation, wet etching, and nanolithography. The integration of these SiNWs into body channel communication (BCC) circuits was also explored. The fabricated SiNWs were confirmed to be capable of forming arrays with multiple layers and rows. The SiNW-based pH sensors demonstrated a robust response to pH changes, and when tested with BCC circuits, they showed that it was possible to quantize based on pH when transmitting data through the human body. This study successfully developed a novel method for SiNW fabrication and integration into BCC circuits, which could lead to improvements in the reliability and efficiency of implantable medical sensors. The findings demonstrate significant potential for bioelectronic applications and real-time biochemical monitoring. Full article
(This article belongs to the Special Issue Selected Papers from IMETI 2022)
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10 pages, 426 KiB  
Article
Assessing the Global Cognition of Community-Dwelling Older Adults Using Motor and Sensory Factors: A Cross-Sectional Feasibility Study
by Emilija Kostic, Kiyoung Kwak and Dongwook Kim
Sensors 2023, 23(17), 7384; https://doi.org/10.3390/s23177384 - 24 Aug 2023
Viewed by 638
Abstract
Impairments in gait, postural stability, and sensory functions were proved to be strongly associated with severe cognitive impairment such as in dementia. However, to prevent dementia, it is necessary to detect cognitive deterioration early, which requires a deeper understanding of the connections between [...] Read more.
Impairments in gait, postural stability, and sensory functions were proved to be strongly associated with severe cognitive impairment such as in dementia. However, to prevent dementia, it is necessary to detect cognitive deterioration early, which requires a deeper understanding of the connections between the aforementioned functions and global cognition. Therefore, the current study measured gait, postural, auditory, and visual functions and, using principal component analysis, explored their individual and cumulative association with global cognition. The global cognitive function of 82 older Korean males was determined using the Montreal Cognitive Assessment. The motor and sensory functions were summarized into seven independent factors using factor analysis, followed by age and education-level-adjusted linear regression model analysis. The seven factors obtained using factor analysis were gait speed, gait stability, midstance, general auditory ability, auditory recognition, overall visual ability, and postural stability. The linear regression model included years of education, gait stability, postural stability, and auditory recognition, and was able to explain more than half of the variability in cognitive score. This shows that motor and sensory parameters, which are obtainable through wearable sensors and mobile applications, could be utilized in detecting cognitive fluctuations even in the early stages of cognitive deterioration. Full article
(This article belongs to the Special Issue Selected Papers from IMETI 2022)
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18 pages, 9437 KiB  
Article
A Morphing Point-to-Point Displacement Control Based on Long Short-Term Memory for a Coplanar XXY Stage
by Ming-Yu Ma, Yi-Cheng Huang and Yu-Tso Wu
Sensors 2023, 23(4), 1938; https://doi.org/10.3390/s23041938 - 09 Feb 2023
Viewed by 1091
Abstract
In this study, visual recognition with a charge-coupled device (CCD) image feedback control system was used to record the movement of a coplanar XXY stage. The position of the stage is fedback through the image positioning method, and the positioning compensation of the [...] Read more.
In this study, visual recognition with a charge-coupled device (CCD) image feedback control system was used to record the movement of a coplanar XXY stage. The position of the stage is fedback through the image positioning method, and the positioning compensation of the stage is performed by the image compensation control parameter. The image resolution was constrained and resulted in an average positioning error of the optimized control parameter of 6.712 µm, with the root mean square error being 2.802 µm, and the settling time being approximately 7 s. The merit of a long short-term memory (LSTM) deep learning model is that it can identify long-term dependencies and sequential state data to determine the next control signal. As for improving the positioning performance, LSTM was used to develop a training model for stage motion with an additional dial indicator with an accuracy of 1 μm being used to record the XXY position information. After removing the assisting dial indicator, a new LSTM-based XXY feedback control system was subsequently constructed to reduce the positioning error. In other words, the morphing control signals are dependent not only on time, but also on the iterations of the LSTM learning process. Point-to-point commanded forward, backward and repeated back-and-forth repetitive motions were conducted. Experimental results revealed that the average positioning error achieved after using the LSTM model was 2.085 µm, with the root mean square error being 2.681 µm, and a settling time of 2.02 s. With the assistance of LSTM, the stage exhibited a higher control accuracy and less settling time than did the CCD imaging system according to three positioning indices. Full article
(This article belongs to the Special Issue Selected Papers from IMETI 2022)
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