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Applications of Advanced Sensors on Applied System Innovation of IoT...
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Applications of Advanced Sensors on Applied System Innovation of IoT (Internet of Things)

A special issue of Applied System Innovation (ISSN 2571-5577).

Deadline for manuscript submissions: closed (30 June 2019) | Viewed by 16786

Special Issue Editors

Prof. Dr. Cheng-Fu Yang

E-Mail Website
Guest Editor
Department of Aeronautical Engineering, Chaoyang University of Technology, Taichung 413, Taiwan
Interests: electronic ceramics; high-frequency communication materials; applied science
Special Issues, Collections and Topics in MDPI journals
Dr. Stephen D. Prior

E-Mail Website
Guest Editor
Aeronautics, Astronautics and Computational Engineering, University of Southampton, Southampton SO16 7QF, UK
Interests: microsystem design; nanotechnology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Internet of Things (IoT) devices offer huge potential for electronic component manufacturers, but their value clearly goes beyond this. Most of the added value in IoT solutions will come from the processing of the generated data. In fact, the ratio between electronic components and data processing can reach 1:50 in certain long-term cases. This is easily understandable, since the main purpose of the IoT is to make sensing ubiquitous at a very low cost, resulting in extremely strong price pressure on electronic component manufacturers. This special issue provides an advanced forum for the science and technology of sensors on applied system innovation of IoT. It publishes reviews (including comprehensive reviews on the complete sensor products) and regular research papers. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. The full experimental details must be provided so that the results can be reproduced. We invite investigators to contribute original research articles, as well as review articles, to this Special Issue.

Potential topics include, but are not limited to:

1. Electrochemical sensors/Biosensors on IoT
2. Electrical- and thermal-based sensors on IoT
3. Mass-sensitive and fiber-optic sensors on IoT
4. Optoelectronic and Photonic Sensors on IoT
5. Gas sensors on IoT
6. Sensor devices and sensor arrays/Nano sensors on IoT
7. Advanced sensors analysis and design for IoT
8. Applied system innovation of advanced sensors on IoT

Prof. Dr. Cheng-Fu Yang
Dr. Stephen D. Prior
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. Applied System Innovation 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 1400 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

  • Advanced sensors on IoT 
  • Advanced sensors analysis and design for IoT 
  • Applied system innovation of advanced sensors on IoT

Published Papers (3 papers)

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Research

28 pages, 2344 KiB  
Article
A Composite and Wearable Sensor Kit for Location-Aware Healthcare Monitoring and Real-Time Trauma Scoring for Survival Prediction
by Amit Walinjkar
Appl. Syst. Innov. 2018, 1(3), 35; https://doi.org/10.3390/asi1030035 - 12 Sep 2018
Cited by 2 | Viewed by 4587
Abstract
With the advances in the microfabrication of analogue front-end devices, and embedded and signal processing technology, it has now become possible to devise miniaturized health monitoring kits for non-invasive real time monitoring at any location. The current commonly available kits only measure singleton [...] Read more.
With the advances in the microfabrication of analogue front-end devices, and embedded and signal processing technology, it has now become possible to devise miniaturized health monitoring kits for non-invasive real time monitoring at any location. The current commonly available kits only measure singleton physiological parameters, and a composite analysis that covers all vital signs and trauma scores seems to be missing with these kits. The research aims at using vital signs and other physiological parameters to calculate trauma scores National Early Warning Score (NEWS), Revised Trauma Score (RTS), Trauma Score - Injury Severity Score (TRISS) and Prediction of survival (Ps), and to log the trauma event to electronic health records using standard coding schemes. The signal processing algorithms were implemented in MATLAB and could be ported to TI AM335x using MATLAB/Embedded Coder. Motion artefacts were removed using a level ‘5’ stationary wavelet transform and a ‘sym4’ wavelet, which yielded a signal-to-noise ratio of 27.83 dB. To demonstrate the operation of the device, an existing Physionet, MIMIC II Numerics dataset was used to calculate NEWS and RTS scores, and to generate the correlation and regression models for a clinical class of patients with respiratory failure and admitted to Intensive Care Unit (ICU). Parameters such as age, heart rate, Systolic Blood Pressure (SysBP), respiratory rate, and Oxygen Saturation (SpO2) as predictors to Ps, showed significant positive regressions of 93% at p < 0.001. The NEWS and RTS scores showed no significant correlation (r = 0.25, p < 0.001) amongst themselves; however, the NEWS and RTS together showed significant correlations with Ps (blunt) (r = 0.70, p < 0.001). RTS and Ps (blunt) scores showed some correlations (r = 0.63, p < 0.001), and the NEWS score showed significant correlation (r = 0.79, p < 0.001) with Ps (blunt) scores. Global Positioning System (GPS) system was built into the kit to locate the individual and to calculate the shortest path to the nearest healthcare center using the Quantum Geographical Information System (QGIS) Network Analysis tool. The physiological parameters from the sensors, along with the calculated trauma scores, were encoded according to a standard Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) coding system, and the trauma information was logged to electronic health records using Fast Health Interoperability Resources (FHIR) servers. The FHIR servers provided interoperable web services to log the trauma event information in real time and to prepare for medical emergencies. Full article
(This article belongs to the Special Issue Applications of Advanced Sensors on Applied System Innovation of IoT (Internet of Things))
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8 pages, 482 KiB  
Article
A System for Controlling and Monitoring IoT Applications
by Zebenzuy Lima, Hugo García-Vázquez, Raúl Rodríguez, Sunil L. Khemchandani, Fortunato Dualibe and Javier Del Pino
Appl. Syst. Innov. 2018, 1(3), 26; https://doi.org/10.3390/asi1030026 - 27 Jul 2018
Cited by 7 | Viewed by 5127
Abstract
In this work, the design and implementation of an open source software and hardware system for Internet of Things (IoT) applications is presented. This system permits the remote monitoring of supplied data from sensors and webcams and the control of different devices such [...] Read more.
In this work, the design and implementation of an open source software and hardware system for Internet of Things (IoT) applications is presented. This system permits the remote monitoring of supplied data from sensors and webcams and the control of different devices such as actuators, servomotors and LEDs. The parameters which have been monitored are brightness, temperature and relative humidity all of which constitute possible environmental factors. The control and monitoring of the installation is realised through a server which is managed by an administrator. The device which rules the installation is a Raspberry Pi, a small and powerful micro-computer in a single board with low consumption, low cost and reconfigurability. Full article
(This article belongs to the Special Issue Applications of Advanced Sensors on Applied System Innovation of IoT (Internet of Things))
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18 pages, 1536 KiB  
Article
Innovation Potentials and Pathways Merging AI, CPS, and IoT
by Matthias Klumpp
Appl. Syst. Innov. 2018, 1(1), 5; https://doi.org/10.3390/asi1010005 - 24 Jan 2018
Cited by 12 | Viewed by 6181
Abstract
Recent advances in the areas of Artificial Intelligence (AI) in the informatics field, Cyber-Physical Systems (CPS) in the production field, and Internet of Things (IoT) in the logistics and transportation field have induced a tremendous growth and innovation potential for global value chain [...] Read more.
Recent advances in the areas of Artificial Intelligence (AI) in the informatics field, Cyber-Physical Systems (CPS) in the production field, and Internet of Things (IoT) in the logistics and transportation field have induced a tremendous growth and innovation potential for global value chain setups. The question is not if further innovation and automation will happen but when—sooner than later—and how. Independent of physical production innovations (additive manufacturing) the information integration and decision autonomy tendencies themselves will drive new supply chain and customer interaction designs and business models. This article presents a technology forecast model based on extensive descriptions of developments by field as well as interaction traits. Results suggest that the crucial element in AI and technology application in logistics will be the human factor and human-artificial cooperation capacities and attitudes. Full article
(This article belongs to the Special Issue Applications of Advanced Sensors on Applied System Innovation of IoT (Internet of Things))
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