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Special Issue "State-of-the-Art Sensors Technology in Greece"

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

Deadline for manuscript submissions: 20 October 2022 | Viewed by 2915

Special Issue Editor

Prof. Dr. Manolis Tsiknakis
E-Mail Website
Guest Editor
Department of Electric and Computer Engineering, Hellenic Mediteranean University and Computational BioMedicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology Hellas (FORTH), Greece
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to provide a comprehensive overview of the current state of the art in sensor technology in Greece. We invite research articles that will consolidate our understanding in this area. The Special Issue will publish full research papers and reviews. Potential topics include, but are not limited to, the following research areas:

  • Advanced materials for sensing;
  • Internet of Things;
  • Industrial sensors and IoT protocols;
  • Physical sensors;
  • Chemical sensors;
  • Biosensors;
  • Remote sensors;
  • Sensor networks;
  • Smart/Intelligent sensors;
  • Sensor devices;
  • Sensor technology and application;
  • Sensing principles;
  • Optoelectronic and photonic sensors;
  • Optomechanical sensors;
  • Sensor arrays and chemometrics;
  • Micro- and nanosensors;
  • Signal processing, data fusion, and deep learning in sensor systems;
  • Sensor interface;
  • Human–Computer Interaction;
  • Sensing systems;
  • MEMS/NEMS;
  • Localization and object tracking.

Prof. Dr. Manolis Tsiknakis
Guest Editor

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 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.

Published Papers (2 papers)

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Research

Article
A Quality Control Methodology for Heterogeneous Vehicular Data Streams
Sensors 2022, 22(4), 1550; https://doi.org/10.3390/s22041550 - 18 Feb 2022
Viewed by 575
Abstract
The rapid evolution of sensors and communication technologies has led to the production and transfer of mass data streams from vehicles either inside their electronic units or to the outside world using the internet infrastructure. The “outside world”, in most cases, consists of [...] Read more.
The rapid evolution of sensors and communication technologies has led to the production and transfer of mass data streams from vehicles either inside their electronic units or to the outside world using the internet infrastructure. The “outside world”, in most cases, consists of third-party applications, such as fleet or traffic management control centers, which utilize vehicular data for reporting and monitoring functionalities. Such applications, in most cases, in order to facilitate their needs, require the exchange and processing of vast amounts of data which can be handled by the so-called Big Data technologies. The purpose of this study is to present a hybrid platform suitable for data collection, storing and analysis enhanced with quality control actions. In particular, the collected data contain various formats originating from different vehicle sensors and are stored in the aforementioned platform in a continuous way. The stored data in this platform must be checked in order to determine and validate them in terms of quality. To do so, certain actions, such as missing values checks, format checks, range checks, etc., must be carried out. The results of the quality control functions are presented herein, and useful conclusions are drawn in order to avoid possible data quality problems which may occur in further analysis and use of the data, e.g., for training of artificial intelligence models. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Greece)
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Article
The Smart-Insole Dataset: Gait Analysis Using Wearable Sensors with a Focus on Elderly and Parkinson’s Patients
Sensors 2021, 21(8), 2821; https://doi.org/10.3390/s21082821 - 16 Apr 2021
Cited by 10 | Viewed by 1804
Abstract
Gait analysis is crucial for the detection and management of various neurological and musculoskeletal disorders. The identification of gait events is valuable for enhancing gait analysis, developing accurate monitoring systems, and evaluating treatments for pathological gait. The aim of this work is to [...] Read more.
Gait analysis is crucial for the detection and management of various neurological and musculoskeletal disorders. The identification of gait events is valuable for enhancing gait analysis, developing accurate monitoring systems, and evaluating treatments for pathological gait. The aim of this work is to introduce the Smart-Insole Dataset to be used for the development and evaluation of computational methods focusing on gait analysis. Towards this objective, temporal and spatial characteristics of gait have been estimated as the first insight of pathology. The Smart-Insole dataset includes data derived from pressure sensor insoles, while 29 participants (healthy adults, elderly, Parkinson’s disease patients) performed two different sets of tests: The Walk Straight and Turn test, and a modified version of the Timed Up and Go test. A neurologist specialized in movement disorders evaluated the performance of the participants by rating four items of the MDS-Unified Parkinson’s Disease Rating Scale. The annotation of the dataset was performed by a team of experienced computer scientists, manually and using a gait event detection algorithm. The results evidence the discrimination between the different groups, and the verification of established assumptions regarding gait characteristics of the elderly and patients suffering from Parkinson’s disease. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Greece)
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