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Special Issue "Selected Papers from the 7th International Electronic Conference on Sensors and Applications"

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: 31 May 2021.

Special Issue Editors

Dr. Stefano Mariani
E-Mail Website
Guest Editor
Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milano, Italy
Interests: MEMS; smart materials; micromechanics; machine learning-driven materials modeling
Special Issues and Collections in MDPI journals
Dr. Stefan Bosse
E-Mail Website
Guest Editor
1. Department of Computer Science, University of Bremen, 28359 Bremen, Germany
2. Faculty Computer Science, University of Koblenz-Landau, 55118 Mainz, Germany
Interests: self-* and intelligent systems; agents; distributed machine learning; multidomain simulation; distributed sensor networks; material informatics; crowd sensing; social data mining
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue comprises extended and expanded versions of proceedings papers from the 7th International Electronic Conference on Sensors and Applications, held 15–30 November 2020, on sciforum.net. In this 7th edition of e-conference, contributors were invited to provide papers and presentations from the field of sensors and applications at large, resulting in a wide variety of excellent submissions and topic areas. Selected papers which attracted the most interest on the web, or that provided a particularly innovative contribution, have been gathered for publication. These papers have been subjected to peer review and are published with the aim of rapid and wide dissemination of research results, developments and applications. We hope this conference series will grow rapidly in the future and become recognized as a new way and venue by which to (electronically) present new developments related to the field of sensors and their applications.

Dr. Stefano Mariani
Dr. Thomas B. Messervey
Dr. Alberto Vallan
Dr. Stefan Bosse
Prof. Dr. Francisco Falcone
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 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 2200 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

  • Biosensors
  • chemical sensors
  • physical sensors
  • sensor networks
  • applications
  • smart cities
  • structural health monitoring technologies and sensor networks
  • wearable sensors
  • optical fiber sensors
  • nanosensors
  • pathogen sensors

Published Papers (2 papers)

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Research

Open AccessArticle
Systematic Performance Evaluation of a Novel Optimized Differential Localization Method for Capsule Endoscopes
Sensors 2021, 21(9), 3180; https://doi.org/10.3390/s21093180 - 03 May 2021
Viewed by 303
Abstract
Capsule endoscopy is a well-established diagnostic tool for the gastrointestinal tract. However, the reliable tracking of capsule endoscopes needs further investigation. Recently, the static magnetic differential method for the localization of capsule endoscopes has shown promising results. This method was experimentally validated by [...] Read more.
Capsule endoscopy is a well-established diagnostic tool for the gastrointestinal tract. However, the reliable tracking of capsule endoscopes needs further investigation. Recently, the static magnetic differential method for the localization of capsule endoscopes has shown promising results. This method was experimentally validated by investigating the difference in the measured values of the geomagnetic flux density of a representative sensor pair. In the measurements, it was revealed that misalignment of the sensors and ferromagnetic material near the sensor pair had the most significant impact on the differential approach. Besides, a systematical simulation-based study was conducted. Herein, the position and alignment of all sensors of the localization system were randomly varied. Furthermore, root-mean-squared noise was added to the sensor measurements, and the influence of nearby ferromagnetic material was evaluated. Subsequently, non-idealities were applied simultaneously on the proposed localization system, and the entire system was rotated. The proposed method was significantly better than state-of-the-art geomagnetic compensation methods for the localization of capsule endoscopes with mean position and orientation errors of approximately 2 mm and 1°, respectively. Full article
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Open AccessArticle
Memetic Chains for Improving the Local Wireless Sensor Networks Localization in Urban Scenarios
Sensors 2021, 21(7), 2458; https://doi.org/10.3390/s21072458 - 02 Apr 2021
Viewed by 369
Abstract
Local Positioning Systems (LPS) have become an active field of research in the last few years. Their application in harsh environments for high-demanded accuracy applications is allowing the development of technological activities such as autonomous navigation, indoor localization, or low-level flights in restricted [...] Read more.
Local Positioning Systems (LPS) have become an active field of research in the last few years. Their application in harsh environments for high-demanded accuracy applications is allowing the development of technological activities such as autonomous navigation, indoor localization, or low-level flights in restricted environments. LPS consists of ad-hoc deployments of sensors which meets the design requirements of each activity. Among LPS, those based on temporal measurements are attracting higher interest due to their trade-off among accuracy, robustness, availability, and costs. The Time Difference of Arrival (TDOA) is extended in the literature for LPS applications and consequently we perform, in this paper, an analysis of the optimal sensor deployment of this architecture for achieving practical results. This is known as the Node Location Problem (NLP) and has been categorized as NP-Hard. Therefore, heuristic solutions such as Genetic Algorithms (GA) or Memetic Algorithms (MA) have been applied in the literature for the NLP. In this paper, we introduce an adaptation of the so-called MA-Solis Wets-Chains (MA-SW-Chains) for its application in the large-scale discrete discontinuous optimization of the NLP in urban scenarios. Our proposed algorithm MA-Variable Neighborhood Descent-Chains (MA-VND-Chains) outperforms the GA and the MA of previous proposals for the NLP, improving the accuracy achieved by 17% and by 10% respectively for the TDOA architecture in the urban scenario introduced. Full article
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