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Advanced Low-Cost Sensing Technology for Exposure and Health Assessments
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Advanced Low-Cost Sensing Technology for Exposure and Health Assessments

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

Deadline for manuscript submissions: 25 August 2024 | Viewed by 2084

Special Issue Editor

Dr. Hamid Omidvarborna

E-Mail Website
Guest Editor
Global Centre for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, Surrey, UK
Interests: low-cost sensors; wearable sensors; air quality; air pollution control; low-cost air pollution monitors; environmental monitoring and assessment; combustion chemistry; energy and environment

Special Issue Information

Dear Colleagues,

Due to advanced low-cost sensing technology, new smart sensors are being introduced every day. This technology provides an alternative way to monitor human exposure and health assessment in real time. For example, wearable sensors can measure individuals’ exposure to surrounding environmental conditions, such as temperature, humidity, and noise, the level of air pollution (both indoor and outdoor), and biological signals, such as heart rate and blood oxygen saturation. These sensors can monitor individuals’ exposure levels to air pollution with high spatiotemporal resolution, which can substantially help end users to better understand their exposure levels during daily activities. Additionally, they can be utilized in advancing and personalizing human health research epidemiological studies and citizen science activities. Recently, this technology has been upgraded and embedded into many commercially available products, such as wristwatches, fitness bands, textile products, and face masks. In this Special Issue, we welcome studies that will help this technology become a part of our routine life. To do so, topics such as sensor design, development, fabrication, calibration, implementation, as well as data analysis and modeling, are welcome.

Dr. Hamid Omidvarborna
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 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

  • low-cost sensors
  • performance evaluation
  • internet of things
  • health monitoring
  • mobile health
  • exposure assessment
  • epidemiological studies

Published Papers (2 papers)

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Research

19 pages, 4191 KiB  
Article
Development of a Unified IoT Platform for Assessing Meteorological and Air Quality Data in a Tropical Environment
by David Kairuz-Cabrera, Victor Hernandez-Rodriguez, Olivier Schalm, Alain Martinez, Pedro Merino Laso and Daniellys Alejo-Sánchez
Sensors 2024, 24(9), 2729; https://doi.org/10.3390/s24092729 - 25 Apr 2024
Viewed by 487
Abstract
In developing nations, outdated technologies and sulfur-rich heavy fossil fuel usage are major contributors to air pollution, affecting urban air quality and public health. In addition, the limited resources hinder the adoption of advanced monitoring systems crucial for informed public health policies. This [...] Read more.
In developing nations, outdated technologies and sulfur-rich heavy fossil fuel usage are major contributors to air pollution, affecting urban air quality and public health. In addition, the limited resources hinder the adoption of advanced monitoring systems crucial for informed public health policies. This study addresses this challenge by introducing an affordable internet of things (IoT) monitoring system capable of tracking atmospheric pollutants and meteorological parameters. The IoT platform combines a Bresser 5-in-1 weather station with a previously developed air quality monitoring device equipped with Alphasense gas sensors. Utilizing MQTT, Node-RED, InfluxDB, and Grafana, a Raspberry Pi collects, processes, and visualizes the data it receives from the measuring device by LoRa. To validate system performance, a 15-day field campaign was conducted in Santa Clara, Cuba, using a Libelium Smart Environment Pro as a reference. The system, with a development cost several times lower than Libelium and measuring a greater number of variables, provided reliable data to address air quality issues and support health-related decision making, overcoming resource and budget constraints. The results showed that the IoT architecture has the capacity to process measurements in tropical conditions. The meteorological data provide deeper insights into events of poorer air quality. Full article
(This article belongs to the Special Issue Advanced Low-Cost Sensing Technology for Exposure and Health Assessments)
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20 pages, 5650 KiB  
Article
A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature
by Marcela E. Mata-Romero, Omar A. Simental-Martínez, Héctor A. Guerrero-Osuna, Luis F. Luque-Vega, Emmanuel Lopez-Neri, Gerardo Ornelas-Vargas, Rodrigo Castañeda-Miranda, Ma. del Rosario Martínez-Blanco, Jesús Antonio Nava-Pintor and Fabián García-Vázquez
Sensors 2024, 24(6), 1944; https://doi.org/10.3390/s24061944 - 18 Mar 2024
Viewed by 1262
Abstract
The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely [...] Read more.
The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning. Full article
(This article belongs to the Special Issue Advanced Low-Cost Sensing Technology for Exposure and Health Assessments)
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