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Intelligent IoT Platforms for Wellbeing

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

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 19131
Please contact the Guest Editor or the Section Managing Editor at ([email protected]) for any queries.

Special Issue Editor


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Guest Editor
Center for Life Science Automation, University Rostock, F.-Barnewitz-Str. 8, 18119 Rostock (D), Germany
Interests: life science automation; robotics; smart sensor systems; mobile robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wellbeing is a holistic bio-psychosocial construct that is not easy to define and measure. A person’s health and energy represent the physical aspect. To objectify wellbeing, suitable measurement parameters must be found. In addition to biological and medical parameters, environmental parameters also have a significant influence. This includes methods of room air monitoring, but also of noise monitoring or the determination of air humidity or radiation parameters. Often, individual parameters are not meaningful in themselves, so that a fusion of sensor data also makes sense using methods of artificial intelligence. Especially in the area of wellbeing, questionnaires are also included in the recording.

This Special Issue encourages authors, from academia and industry, to submit new research results about technological innovations and novel applications for monitoring biological, medical, and ambient parameters for the objectification of wellbeing. 

Prof. Dr. Kerstin Thurow
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

The Special Issue topics should cover all possible aspects. These include but are not limited to:

  • New applications for smart monitoring IoT platforms for wellbeing
  • Sensors for environmental monitoring (gases, chemicals, noise, radiation, etc.)
  • Sensors for monitoring “wellbeing” parameters
  • Wearable sensors
  • Sensor miniaturization
  • Sensor fusion approaches
  • Novel technologies
  • Artificial Intelligence approaches for IoT platforms for wellbeing
  • State-of-the-art devices
  • Challenges in design and deployment
  • Evaluation of smart sensor approaches for wellbeing.

Published Papers (4 papers)

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Research

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10 pages, 2132 KiB  
Article
An Instrumented Apartment to Monitor Human Behavior: A Pilot Case Study in the NeuroTec Loft
by Stephan M. Gerber, Michael Single, Samuel E. J. Knobel, Narayan Schütz, Lena C. Bruhin, Angela Botros, Aileen C. Naef, Kaspar A. Schindler and Tobias Nef
Sensors 2022, 22(4), 1657; https://doi.org/10.3390/s22041657 - 20 Feb 2022
Cited by 2 | Viewed by 2306
Abstract
For patients suffering from neurodegenerative disorders, the behavior and activities of daily living are an indicator of a change in health status, and home-monitoring over a prolonged period of time by unobtrusive sensors is a promising technology to foster independent living and maintain [...] Read more.
For patients suffering from neurodegenerative disorders, the behavior and activities of daily living are an indicator of a change in health status, and home-monitoring over a prolonged period of time by unobtrusive sensors is a promising technology to foster independent living and maintain quality of life. The aim of this pilot case study was the development of a multi-sensor system in an apartment to unobtrusively monitor patients at home during the day and night. The developed system is based on unobtrusive sensors using basic technologies and gold-standard medical devices measuring physiological (e.g., mobile electrocardiogram), movement (e.g., motion tracking system), and environmental parameters (e.g., temperature). The system was evaluated during one session by a healthy 32-year-old male, and results showed that the sensor system measured accurately during the participant’s stay. Furthermore, the participant did not report any negative experiences. Overall, the multi-sensor system has great potential to bridge the gap between laboratories and older adults’ homes and thus for a deep and novel understanding of human behavioral and neurological disorders. Finally, this new understanding could be utilized to develop new algorithms and sensor systems to address problems and increase the quality of life of our aging society and patients with neurological disorders. Full article
(This article belongs to the Special Issue Intelligent IoT Platforms for Wellbeing)
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22 pages, 90335 KiB  
Article
Flexible IoT Gas Sensor Node for Automated Life Science Environments Using Stationary and Mobile Robots
by Sebastian Neubert, Thomas Roddelkopf, Mohammed Faeik Ruzaij Al-Okby, Steffen Junginger and Kerstin Thurow
Sensors 2021, 21(21), 7347; https://doi.org/10.3390/s21217347 - 04 Nov 2021
Cited by 14 | Viewed by 3644
Abstract
In recent years the degree of automation in life science laboratories increased considerably by introducing stationary and mobile robots. This trend requires intensified considerations of the occupational safety for cooperating humans, since the robots operate with low volatile compounds that partially emit hazardous [...] Read more.
In recent years the degree of automation in life science laboratories increased considerably by introducing stationary and mobile robots. This trend requires intensified considerations of the occupational safety for cooperating humans, since the robots operate with low volatile compounds that partially emit hazardous vapors, which especially do arise if accidents or leakages occur. For the fast detection of such or similar situations a modular IoT-sensor node was developed. The sensor node consists of four hardware layers, which can be configured individually regarding basic functionality and measured parameters for varying application focuses. In this paper the sensor node is equipped with two gas sensors (BME688, SGP30) for a continuous TVOC measurement. In investigations under controlled laboratory conditions the general sensors’ behavior regarding different VOCs and varying installation conditions are performed. In practical investigations the sensor node’s integration into simple laboratory applications using stationary and mobile robots is shown and examined. The investigation results show that the selected sensors are suitable for the early detection of solvent vapors in life science laboratories. The sensor response and thus the system’s applicability depends on the used compounds, the distance between sensor node and vapor source as well as the speed of the automation systems. Full article
(This article belongs to the Special Issue Intelligent IoT Platforms for Wellbeing)
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Review

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20 pages, 2880 KiB  
Review
Mobile Detection and Alarming Systems for Hazardous Gases and Volatile Chemicals in Laboratories and Industrial Locations
by Mohammed Faeik Ruzaij Al-Okby, Sebastian Neubert, Thomas Roddelkopf and Kerstin Thurow
Sensors 2021, 21(23), 8128; https://doi.org/10.3390/s21238128 - 04 Dec 2021
Cited by 16 | Viewed by 5084
Abstract
The leakage of hazardous gases and chemical vapors is considered one of the dangerous accidents that can occur in laboratories, workshops, warehouses, and industrial sites that use or store these substances. The early detection and alarming of hazardous gases and volatile chemicals are [...] Read more.
The leakage of hazardous gases and chemical vapors is considered one of the dangerous accidents that can occur in laboratories, workshops, warehouses, and industrial sites that use or store these substances. The early detection and alarming of hazardous gases and volatile chemicals are significant to keep the safety conditions for the people and life forms who are work in and live around these places. In this paper, we investigate the available mobile detection and alarming systems for toxic, hazardous gases and volatile chemicals, especially in the laboratory environment. We included papers from January 2010 to August 2021 which may have the newest used sensors technologies and system components. We identified (236) papers from Clarivate Web of Science (WoS), IEEE, ACM Library, Scopus, and PubMed. Paper selection has been done based on a fast screening of the title and abstract, then a full-text reading was applied to filter the selected papers that resulted in (42) eligible papers. The main goal of this work is to discuss the available mobile hazardous gas detection and alarming systems based on several technical details such as the used gas detection technology (simple element, integrated, smart, etc.), sensor manufacturing technology (catalytic bead, MEMS, MOX, etc.) the sensor specifications (warm-up time, lifetime, response time, precision, etc.), processor type (microprocessor, microcontroller, PLC, etc.), and type of the used communication technology (Bluetooth/BLE, Wi-Fi/RF, ZigBee/XBee, LoRa, etc.). In this review, attention will be focused on the improvement of the detection and alarming system of hazardous gases with the latest invention in sensors, processors, communication, and battery technologies. Full article
(This article belongs to the Special Issue Intelligent IoT Platforms for Wellbeing)
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24 pages, 7283 KiB  
Review
Wearable Devices in Health Monitoring from the Environmental towards Multiple Domains: A Survey
by Mostafa Haghi, Saeed Danyali, Sina Ayasseh, Ju Wang, Rahmat Aazami and Thomas M. Deserno
Sensors 2021, 21(6), 2130; https://doi.org/10.3390/s21062130 - 18 Mar 2021
Cited by 31 | Viewed by 6727
Abstract
The World Health Organization (WHO) recognizes the environmental, behavioral, physiological, and psychological domains that impact adversely human health, well-being, and quality of life (QoL) in general. The environmental domain has significant interaction with the others. With respect to proactive and personalized medicine and [...] Read more.
The World Health Organization (WHO) recognizes the environmental, behavioral, physiological, and psychological domains that impact adversely human health, well-being, and quality of life (QoL) in general. The environmental domain has significant interaction with the others. With respect to proactive and personalized medicine and the Internet of medical things (IoMT), wearables are most important for continuous health monitoring. In this work, we analyze wearables in healthcare from a perspective of innovation by categorizing them according to the four domains. Furthermore, we consider the mode of wearability, costs, and prolonged monitoring. We identify features and investigate the wearable devices in the terms of sampling rate, resolution, data usage (propagation), and data transmission. We also investigate applications of wearable devices. Web of Science, Scopus, PubMed, IEEE Xplore, and ACM Library delivered wearables that we require to monitor at least one environmental parameter, e.g., a pollutant. According to the number of domains, from which the wearables record data, we identify groups: G1, environmental parameters only; G2, environmental and behavioral parameters; G3, environmental, behavioral, and physiological parameters; and G4 parameters from all domains. In total, we included 53 devices of which 35, 9, 9, and 0 belong to G1, G2, G3, and G4, respectively. Furthermore, 32, 11, 7, and 5 wearables are applied in general health and well-being monitoring, specific diagnostics, disease management, and non-medical. We further propose customized and quantified output for future wearables from both, the perspectives of users, as well as physicians. Our study shows a shift of wearable devices towards disease management and particular applications. It also indicates the significant role of wearables in proactive healthcare, having capability of creating big data and linking to external healthcare systems for real-time monitoring and care delivery at the point of perception. Full article
(This article belongs to the Special Issue Intelligent IoT Platforms for Wellbeing)
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