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Innovative Life-Changing Using IoT Sensors
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Innovative Life-Changing Using IoT Sensors

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

Deadline for manuscript submissions: closed (1 August 2021) | Viewed by 10006

Special Issue Editors

Prof. Dr. Hwa-Young Jeong

E-Mail Website
Guest Editor
Humanitas College, Kyung Hee University, Seoul 130-701, Republic of Korea
Interests: image data processing; multimedia based e-learning system and services; conversion service with multimedia; big data analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Yan Pei

E-Mail Website
Guest Editor
School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu 965-8580, Japan
Interests: computational intelligence; machine learning; optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Today, the Internet of Things (IoT) is one of the most popular technologies, and it still brings a completely new perspective on the further progress of various fields for human life. The main goal of IoT is to ensure a better efficiency of systems or services, including specific processes, and to help to improve life quality. It can change the process for energy and environment, smart city, e-health, home automation, etc. IoT technology uses many sensors to gather data and information from sensorial application, sensor devices, and networks that are able to collect a large volume of data. It also improves our lifestyle in terms of efficiency and convenience without human–computer interaction. This Special Issue calls for high-quality, up-to-date research related to innovative life-changing using IoT sensors. In particular, the Special Issue is going to showcase the most recent achievements, developments or services in the field. All submitted papers will be peer-reviewed and selected on the basis of both their quality and their relevance to the theme of this Special Issue.

Prof. Dr. Hwa-Young Jeong
Prof. Dr. Yan Pei
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

  • IoT sensor network
  • Wireless sensor network with IoT
  • Application using IoT
  • Live demonstration of sensors and sensing technologies
  • IoT communication technologies
  • Human interaction with IoT
  • AI and IoT
  • E-health system and service with IoT

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Published Papers (3 papers)

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Research

21 pages, 5784 KiB  
Article
Multi-Blockchain-Based IoT Data Processing Techniques to Ensure the Integrity of IoT Data in AIoT Edge Computing Environments
by Sung-Ho Sim and Yoon-Su Jeong
Sensors 2021, 21(10), 3515; https://doi.org/10.3390/s21103515 - 18 May 2021
Cited by 20 | Viewed by 3839
Abstract
As the development of IoT technologies has progressed rapidly recently, most IoT data are focused on monitoring and control to process IoT data, but the cost of collecting and linking various IoT data increases, requiring the ability to proactively integrate and analyze collected [...] Read more.
As the development of IoT technologies has progressed rapidly recently, most IoT data are focused on monitoring and control to process IoT data, but the cost of collecting and linking various IoT data increases, requiring the ability to proactively integrate and analyze collected IoT data so that cloud servers (data centers) can process smartly. In this paper, we propose a blockchain-based IoT big data integrity verification technique to ensure the safety of the Third Party Auditor (TPA), which has a role in auditing the integrity of AIoT data. The proposed technique aims to minimize IoT information loss by multiple blockchain groupings of information and signature keys from IoT devices. The proposed technique allows IoT information to be effectively guaranteed the integrity of AIoT data by linking hash values designated as arbitrary, constant-size blocks with previous blocks in hierarchical chains. The proposed technique performs synchronization using location information between the central server and IoT devices to manage the cost of the integrity of IoT information at low cost. In order to easily control a large number of locations of IoT devices, we perform cross-distributed and blockchain linkage processing under constant rules to improve the load and throughput generated by IoT devices. Full article
(This article belongs to the Special Issue Innovative Life-Changing Using IoT Sensors)
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18 pages, 3930 KiB  
Article
Hierarchical Multipath Blockchain Based IoT Information Management Techniques for Efficient Distributed Processing of Intelligent IoT Information
by Yoon-Su Jeong and Sung-Ho Sim
Sensors 2021, 21(6), 2049; https://doi.org/10.3390/s21062049 - 14 Mar 2021
Cited by 1 | Viewed by 2417
Abstract
As cloud technology advances, devices such as IoT (Internet of Things) are being utilized in various areas ranging from transportation, manufacturing, energy, automation, space, defense, and healthcare. As the number of IoT devices increases, the safety of IoT information, which is vulnerable to [...] Read more.
As cloud technology advances, devices such as IoT (Internet of Things) are being utilized in various areas ranging from transportation, manufacturing, energy, automation, space, defense, and healthcare. As the number of IoT devices increases, the safety of IoT information, which is vulnerable to cyber attacks, is emerging as an important area of interest in distributed cloud environments. However, integrity techniques are not guaranteed to easily identify the integrity threats and attacks on IoT information operating in the distributed cloud associated with IoT systems and CPS (Cyber-Physical System). In this paper, we propose a blockchain-based integrity verification technique in which large amounts of IoT information processed in distributed cloud environments can be guaranteed integrity in security threats related to IoT systems and CPS. The proposed technique aims to ensure the integrity of IoT information by linking information from IoT devices belonging to subgroups in distributed cloud environments to information from specific non-adjacent IoT devices and blockchain. This is because existing techniques rely on third-party organizations that the data owner can trust to verify the integrity of the data. The proposed technique identifies IoT information by connecting the paths of IoT pre- and subsequent blocks into block chains so that synchronization can be achieved between subgroups in distributed cloud environments. Furthermore, the proposed technique uses probabilistic similarity information between IoT information blocks to react flexibly to subgroups that constitute distributed clouds so that IoT information blocks are not exploited maliciously by third parties. As a result of performance evaluation, the proposed technique averaged 12.3% improvement in integrity processing time over existing techniques depending on blockchain size. Furthermore, the proposed technique has to hash the IoT information that constitutes a subgroup with probability-linked information, validating the integrity of large-capacity IoT information, resulting in an average of 8.8% lower overhead than existing techniques. In addition, the proposed technique has an average improvement of 14.3% in blockchain-based integrity verification accuracy over existing techniques, depending on the hash chain length. Full article
(This article belongs to the Special Issue Innovative Life-Changing Using IoT Sensors)
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15 pages, 2860 KiB  
Article
User Recommendation for Data Sharing in Social Internet of Things
by Kyoungsoo Bok, Yeondong Kim, Dojin Choi and Jaesoo Yoo
Sensors 2021, 21(2), 462; https://doi.org/10.3390/s21020462 - 11 Jan 2021
Cited by 12 | Viewed by 2792
Abstract
As various types of data are generated on the social Internet of things (SIoT), which combine the Internet of things (IoT) and social networks, the relations of IoT devices should be established for necessary data exchange. In this paper, we propose a user [...] Read more.
As various types of data are generated on the social Internet of things (SIoT), which combine the Internet of things (IoT) and social networks, the relations of IoT devices should be established for necessary data exchange. In this paper, we propose a user recommendation scheme that facilitates data sharing through an analysis of an interaction between an IoT device and a user in the SIoT. An interrelation between a user and an IoT device as well as an interrelation between users exist simultaneously in the SIoT. Hence, the interaction between users must be analyzed to identify the interest keywords, and the interaction between IoT devices and users to determine the user’s preference of IoT device. Moreover, the proposed scheme calculates the similarity between users based on the IoT device preference based on IoT device usage frequency and interest keywords, which are identified through an analysis between the user and IoT device and that between users. Subsequently, it recommends top-N users who have a high similarity as the users for data sharing. Furthermore, the performance of the proposed scheme is verified through performance evaluation based on the precision, recall, and F-measure. Full article
(This article belongs to the Special Issue Innovative Life-Changing Using IoT Sensors)
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