IoT Technology in Bioengineering Applications

A special issue of Bioengineering (ISSN 2306-5354).

Deadline for manuscript submissions: 31 July 2024 | Viewed by 3630

Special Issue Editors

Electronic and Telecommunication Department, Constanta Maritime University, Constanța, Romania
Interests: electronic embedded systems; intelligent sensors and interface; smart home; Machine learning; deep learning

Special Issue Information

Dear Colleagues,

This Special Issue presents novel solutions to challenging real-world problems applying IoT devices to bioengineering. IoT technology is used in therapies, implants, diagnostics, adaptive prosthetics, etc., where data are recorded and processed in the cloud for Internet-based uses. This method was developed for remote monitoring to improve people's lives. At the same time, eco plants and biofoods greatly impact human health. IoT technology is used to monitor and diagnose farms and food to improve the nutrient and food quality.

The "IoT Technology in Bioengineering Applications" issue publishes research using quantitative tools, including simulation and mathematical modeling. This Special Issue focuses on exciting applications for bioengineering science in health, medicine, and agronomy.

Dr. Mihaela Hnatiuc
Prof. Dr. Larbi Boubchir
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. Bioengineering is an international peer-reviewed open access monthly 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 2700 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

  • robotic device
  • signal processing
  • image processing
  • communication protocol
  • embedded system
  • smart sensors
  • cloud/FOG
  • predictive methods
  • monitoring
  • process optimization
  • diagnosis
  • implant
  • tele surgery
  • teleconsultation
  • telemonitoring

Published Papers (2 papers)

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Research

16 pages, 3770 KiB  
Article
Intelligent Grapevine Disease Detection Using IoT Sensor Network
by Mihaela Hnatiuc, Simona Ghita, Domnica Alpetri, Aurora Ranca, Victoria Artem, Ionica Dina, Mădălina Cosma and Mazin Abed Mohammed
Bioengineering 2023, 10(9), 1021; https://doi.org/10.3390/bioengineering10091021 - 29 Aug 2023
Cited by 3 | Viewed by 980
Abstract
The Internet of Things (IoT) has gained significance in agriculture, using remote sensing and machine learning to help farmers make high-precision management decisions. This technology can be applied in viticulture, making it possible to monitor disease occurrence and prevent them automatically. The study [...] Read more.
The Internet of Things (IoT) has gained significance in agriculture, using remote sensing and machine learning to help farmers make high-precision management decisions. This technology can be applied in viticulture, making it possible to monitor disease occurrence and prevent them automatically. The study aims to achieve an intelligent grapevine disease detection method, using an IoT sensor network that collects environmental and plant-related data. The focus of this study is the identification of the main parameters which provide early information regarding the grapevine’s health. An overview of the sensor network, architecture, and components is provided in this paper. The IoT sensors system is deployed in the experimental plots located within the plantations of the Research Station for Viticulture and Enology (SDV) in Murfatlar, Romania. Classical methods for disease identification are applied in the field as well, in order to compare them with the sensor data, thus improving the algorithm for grapevine disease identification. The data from the sensors are analyzed using Machine Learning (ML) algorithms and correlated with the results obtained using classical methods in order to identify and predict grapevine diseases. The results of the disease occurrence are presented along with the corresponding environmental parameters. The error of the classification system, which uses a feedforward neural network, is 0.05. This study will be continued with the results obtained from the IoT sensors tested in vineyards located in other regions. Full article
(This article belongs to the Special Issue IoT Technology in Bioengineering Applications)
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26 pages, 5282 KiB  
Article
Securing Group Patient Communication in 6G-Aided Dynamic Ubiquitous Healthcare with Real-Time Mobile DNA Sequencing
by Tuan-Vinh Le
Bioengineering 2023, 10(7), 839; https://doi.org/10.3390/bioengineering10070839 - 15 Jul 2023
Viewed by 1440
Abstract
(1) Background: With an advanced technique, third-generation sequencing (TGS) provides services with long deoxyribonucleic acid (DNA) reads and super short sequencing time. It enables onsite mobile DNA sequencing solutions for enabling ubiquitous healthcare (U-healthcare) services with modern mobile technology and smart entities in [...] Read more.
(1) Background: With an advanced technique, third-generation sequencing (TGS) provides services with long deoxyribonucleic acid (DNA) reads and super short sequencing time. It enables onsite mobile DNA sequencing solutions for enabling ubiquitous healthcare (U-healthcare) services with modern mobile technology and smart entities in the internet of living things (IoLT). Due to some strict requirements, 6G technology can efficiently facilitate communications in a truly intelligent U-healthcare IoLT system. (2) Research problems: conventional single user–server architecture is not able to enable group conversations where “multiple patients–server” communication or “patient–patient” communication in the group is required. The communications are carried out via the open Internet, which is not a trusted channel. Since heath data and medical information are very sensitive, security and privacy concerns in the communication systems have become extremely important. (3) Purpose: the author aims to propose a dynamic group-based patient-authenticated key distribution protocol for 6G-aided U-healthcare services enabled by mobile DNA sequencing. In the protocol, an authenticated common session key is distributed by the server to the patients. Using the key, patients in a healthcare group are allowed to securely connect with the service provider or with each other for specific purposes of communication. (4) Results: the group key distribution process is protected by a secure three-factor authentication mechanism along with an efficient sequencing-device-based single sign-on (SD-SSO) solution. Based on traceable information stored in the server database, the proposed approach can provide patient-centered services which are available on multiple mobile devices. Security robustness of the proposed protocol is proven by well-known verification tools and a detailed semantic discussion. Performance evaluation shows that the protocol provides more functionality and incurs a reasonable overhead in comparison with the existing works. Full article
(This article belongs to the Special Issue IoT Technology in Bioengineering Applications)
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