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Sensors for Environmental and Human Health
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Sensors for Environmental and Human Health

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

Deadline for manuscript submissions: closed (22 September 2022) | Viewed by 8295

Special Issue Editors

Dr. Nenad Gligoric

E-Mail Website
Guest Editor
Zentrix Lab, 26000 Pancevo, Serbia
Interests: iot; circular economy; product passport; printed sensors; functional ink; ontology; mobile computing
Special Issues, Collections and Topics in MDPI journals
Dr. Suparna De

E-Mail Website
Guest Editor
Department of Computer Science, University of Surrey, Guildford GU2 7XH, UK
Interests: deep learning; knowledge modelling and distributed reasoning approaches; Big Data; service computing and pervasive computing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Klaus Moessner

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, Institute for Communication Systems, University of Surrey, Guildford GU2 7XH, Surrey, UK
Interests: cognitive networks; IoT deployments; sensor data based knowledge generation
Special Issues, Collections and Topics in MDPI journals
Dr. Charmi Chande

E-Mail Website
Guest Editor
Visiting Research Scientist, New Jersey Institute of Technology, Newark, NJ, USA
Interests: microfluidics; electrochemical sensors; point-of-use devices; PFAS screening
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleague,

The aim of this Special Issue is to present the latest research findings on development and application of sensor technologies in measurements of environment and human health and well-being. Authors are encouraged to submit non-published and novel manuscripts, as well as survey papers for publication on the following areas:

  • Sensors for environmental monitoring, such as (but not limited to) various environment parameters from air, aqueous, and solid matrices, sensors for detection of emerging contaminants, toxins, etc.;
  • Sensors for human health and well-being monitoring, including (but not limited to) physical body parameters (temperature, heart rate, oxygen), motion recognition and tracking, urine and blood analysis, etc.;
  • Sensors for detection of various viruses, such as (but not limited to) coronaviruses;
  • Novel Internet of Things application in human and/ or environmental monitoring, e.g., healthy aging, in situ real-time monitoring of environmental parameters, etc.;
  • Technical challenges in assuring accuracy and robustness of the provided measures (i.e., sensor placement, measurement drift, repeatability of the provided measures);

Dr. Nenad Gligoric
Dr. Suparna De
Prof. Dr. Klaus Moessner
Dr. Charmi Chande
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

  • Sensors
  • nanosensors
  • biosensors
  • electrochemical sensors
  • environmental sensors
  • IoT
  • PFAS
  • coronaviruses
  • SARS-COV-2
  • well-being

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

29 pages, 11123 KiB  
Article
Evaluation of Commercial Corrosion Sensors for Real-Time Monitoring of Pipe Wall Thickness under Various Operational Conditions
by Dong-Ho Shin, Hyun-Kyu Hwang, Heon-Hui Kim and Jung-Hyung Lee
Sensors 2022, 22(19), 7562; https://doi.org/10.3390/s22197562 - 6 Oct 2022
Cited by 6 | Viewed by 2272
Abstract
In this study, we investigated the performance and reliability of commercial corrosion sensors for monitoring the integrity of piping systems in various fluid environments as an alternative to ultrasonic transducers. To this end, we investigated pipes’ wall-thinning using commercial electrical resistance (ER), linear [...] Read more.
In this study, we investigated the performance and reliability of commercial corrosion sensors for monitoring the integrity of piping systems in various fluid environments as an alternative to ultrasonic transducers. To this end, we investigated pipes’ wall-thinning using commercial electrical resistance (ER), linear polarization resistance (LPR), and ultrasonic transducer (UT) sensors under various operating environments. A pilot-scale closed-loop test bed was built to simulate a real pipeline flow situation, from which the sensor data were collected and analyzed. Experimental results indicate that, in the case of the LPR sensor, it is challenging to accurately measure the corrosion rate when a specific measure exceeds the threshold in a severe corrosion environment. In contrast, the ER sensor could measure metal loss under all conditions and reflect the corresponding characteristics. The metal loss (about 0.25 mm) of the real pipe after the experiment was confirmed to be equal to the metal loss (0.254 mm) measured by the sensor. Furthermore, the regression analysis revealed a high correlation between the results obtained from the ER and UT sensors. Thus, evaluating the remaining thickness of the piping system using the commercial ER sensor is deemed to be effective and reliable. Full article
(This article belongs to the Special Issue Sensors for Environmental and Human Health)
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25 pages, 7192 KiB  
Article
An Edge Computing and Ambient Data Capture System for Clinical and Home Environments
by Pradyumna Byappanahalli Suresha, Chaitra Hegde, Zifan Jiang and Gari D. Clifford
Sensors 2022, 22(7), 2511; https://doi.org/10.3390/s22072511 - 25 Mar 2022
Cited by 3 | Viewed by 4509
Abstract
The non-contact patient monitoring paradigm moves patient care into their homes and enables long-term patient studies. The challenge, however, is to make the system non-intrusive, privacy-preserving, and low-cost. To this end, we describe an open-source edge computing and ambient data capture system, developed [...] Read more.
The non-contact patient monitoring paradigm moves patient care into their homes and enables long-term patient studies. The challenge, however, is to make the system non-intrusive, privacy-preserving, and low-cost. To this end, we describe an open-source edge computing and ambient data capture system, developed using low-cost and readily available hardware. We describe five applications of our ambient data capture system. Namely: (1) Estimating occupancy and human activity phenotyping; (2) Medical equipment alarm classification; (3) Geolocation of humans in a built environment; (4) Ambient light logging; and (5) Ambient temperature and humidity logging. We obtained an accuracy of 94% for estimating occupancy from video. We stress-tested the alarm note classification in the absence and presence of speech and obtained micro averaged F1 scores of 0.98 and 0.93, respectively. The geolocation tracking provided a room-level accuracy of 98.7%. The root mean square error in the temperature sensor validation task was 0.3°C and for the humidity sensor, it was 1% Relative Humidity. The low-cost edge computing system presented here demonstrated the ability to capture and analyze a wide range of activities in a privacy-preserving manner in clinical and home environments and is able to provide key insights into the healthcare practices and patient behaviors. Full article
(This article belongs to the Special Issue Sensors for Environmental and Human Health)
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