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Special Issue "Selected Papers from IEEE ICKII 2020"

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

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Prof. Dr. Teen­-Hang Meen
Guest Editor
Department of Electronic Engineering National Formosa University, Yunlin 632, Taiwan
Interests: photovoltaic device; dye-sensitized solar cells; nanotechnology
Special Issues and Collections in MDPI journals
Prof. Dr. Wenbing Zhao
Guest Editor
Department of Electrical Engineering and Computer Science, Cleveland State University, Ohio, 44011, USA
Interests: human computer interaction; rehabilitation; computer vision; distributed systems
Special Issues and Collections in MDPI journals
Prof. Dr. Hsien-Wei Tseng
Guest Editor
School of Mathematics and Information Engineering, Longyan University, Longyan, Fujian, China
Interests: IoT Implementation; AI Application; Data Mining; Wireless Communication System

Special Issue Information

The 3rd IEEE International Conference on Knowledge Innovation and Invention 2020 (IEEE ICKII 2020, will be held in Busan, South Korea on 24–27 July 2020, and it will provide a unified communication platform for researchers on the topics of information technology, innovation design, communication science and engineering, industrial design, creative design, applied mathematics, computer science, electrical and electronic engineering, mechanical and automation engineering, green technology and architecture engineering, material science, and other related fields. The Special Issue on “Selected papers from IEEE ICKII 2020” is expected to select excellent papers presented in IEEE ICKII 2020 and other high-quality papers about the topics of sensors in science and technology. It publishes reviews (including comprehensive reviews on the complete sensors products) and regular research papers. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. The full experimental details must be provided so that the results can be reproduced. We invite investigators to contribute original research articles, as well as review articles, to this Special Issue. Potential topics include but are not limited to:

  • Electrochemical sensors/biosensors;
  • Electrical and thermal-based sensors;
  • Mass-sensitive and fiber-optic sensors;
  • Optoelectronic and photonic sensors;
  • Gas sensors;
  • Sensor applications for food industry, medicine, pharmacy, environmental monitoring, corrosion, etc.;
  • Sensor devices and sensor arrays/nanosensors;
  • Analytical methods, modeling, readout, and software for sensors;
  • Sensor technology and new sensor principles.

Prof. Dr. Teen­-Hang Meen
Prof. Dr. Wenbing Zhao
Prof. Dr. Hsien-Wei Tseng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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 papers will be 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 2000 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.


  • Electrochemical sensors/biosensors
  • Electrical and thermal-based sensors
  • Mass-sensitive and fiber-optic sensors
  • Optoelectronic and photonic sensors
  • Gas sensors

Published Papers (1 paper)

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Open AccessArticle
A Real-Time Speech Separation Method Based on Camera and Microphone Array Sensors Fusion Approach
Sensors 2020, 20(12), 3527; - 22 Jun 2020
In the context of assisted human, identifying and enhancing non-stationary speech targets speech in various noise environments, such as a cocktail party, is an important issue for real-time speech separation. Previous studies mostly used microphone signal processing to perform target speech separation and [...] Read more.
In the context of assisted human, identifying and enhancing non-stationary speech targets speech in various noise environments, such as a cocktail party, is an important issue for real-time speech separation. Previous studies mostly used microphone signal processing to perform target speech separation and analysis, such as feature recognition through a large amount of training data and supervised machine learning. The method was suitable for stationary noise suppression, but relatively limited for non-stationary noise and difficult to meet the real-time processing requirement. In this study, we propose a real-time speech separation method based on an approach that combines an optical camera and a microphone array. The method was divided into two stages. Stage 1 used computer vision technology with the camera to detect and identify interest targets and evaluate source angles and distance. Stage 2 used beamforming technology with microphone array to enhance and separate the target speech sound. The asynchronous update function was utilized to integrate the beamforming control and speech processing to reduce the effect of the processing delay. The experimental results show that the noise reduction in various stationary and non-stationary noise environments were 6.1 dB and 5.2 dB respectively. The response time of speech processing was less than 10ms, which meets the requirements of a real-time system. The proposed method has high potential to be applied in auxiliary listening systems or machine language processing like intelligent personal assistant. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICKII 2020)
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