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Internet of Things, Smart Sensing and Data Fusion in Smart City

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

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 10393

Special Issue Editor

Special Issue Information

Dear Colleagues,

Rapid advances in the manufacturing of smart sensor nodes have expanded the range of wireless sensor networks (WSNs) applications in Internet-of-Things (IoT) networks, such as monitoring and gathering information from public infrastructure, natural disaster relief, healthcare, smart homes, and industries in smart cities. Smart sensing and data fusion include various smart city applications, offering significant advantages over traditional networks, and leading to a revolution in the perception of information by self-organizing, distributed, low-cost, and power. Many factors may affect the design of a smart city network, including but not limited to cost, power, topology, scalability, reliability, energy consumption, and operating environment. Meanwhile, computational intelligence (CI) is a source of artificial intelligence, and includes techniques such as deep learning, evolutionary algorithms, and fuzzy logic. To address challenges such as localization, optimal deployment, security, energy-aware routing and task scheduling, and data aggregation and fusion, CI paradigms have been successfully used in recent years. In complex and dynamic smart city environments, CI provides adaptive mechanisms that exhibit intelligent behaviors. It offers flexibility, autonomous behavior, and robustness against topology changes, communication failures, and scenario changes.

This Special Issue expects innovative work to explore new frontiers and challenges in the field of IoT, smart sensing, and data fusion research, including optimal usage and management of energy resources, node deployment, applications, and services for scalable smart city networks.

Prof. Dr. James (Jong Hyuk) Park
Guest Editor

Manuscript Submission Information

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Keywords

  • Data Fusion
  • Distributed network
  • Edge computing
  • Internet of Things
  • Software-defined network
  • Smart sensing
  • Deep learning
  • Blockchain security

Published Papers (3 papers)

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Research

19 pages, 8273 KiB  
Article
Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State
by Changhao Piao, Jun Zhang, KyungHi Chang, Yan Li and Mingjie Liu
Sensors 2021, 21(7), 2261; https://doi.org/10.3390/s21072261 - 24 Mar 2021
Cited by 4 | Viewed by 5401
Abstract
The goal of automatic parking system is to accomplish the vehicle parking to the specified space automatically. It mainly includes parking space recognition, parking space matching, and trajectory generation. It has been developed enormously, but it is still a challenging work due to [...] Read more.
The goal of automatic parking system is to accomplish the vehicle parking to the specified space automatically. It mainly includes parking space recognition, parking space matching, and trajectory generation. It has been developed enormously, but it is still a challenging work due to parking space recognition error and trajectory generation for vehicle nonparallel initial state with parking space. In this study, the authors propose multi-sensor information ensemble for parking space recognition and adaptive trajectory generation method, which is also robust to vehicle nonparallel initial state. Both simulation and real vehicle experiments are conducted to prove that the proposed method can improve the automatic parking system performance. Full article
(This article belongs to the Special Issue Internet of Things, Smart Sensing and Data Fusion in Smart City)
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17 pages, 2841 KiB  
Article
A Two-Class Data Transmission Method Using a Lightweight Blockchain Structure for Secure Smart Dust IoT Environments
by Joonsuu Park and KeeHyun Park
Sensors 2020, 20(21), 6078; https://doi.org/10.3390/s20216078 - 26 Oct 2020
Cited by 5 | Viewed by 2163
Abstract
In smart dust IoT environments, a large number of devices with low computing power/resources are deployed to collect surrounding information. There are many issues to consider for an efficient and secure smart dust IoT environment. Sometimes the urgent sensed data needs to be [...] Read more.
In smart dust IoT environments, a large number of devices with low computing power/resources are deployed to collect surrounding information. There are many issues to consider for an efficient and secure smart dust IoT environment. Sometimes the urgent sensed data needs to be transmitted immediately. In addition, there are potential problems related to security issues since the smart dust IoT systems may be deployed in hard-to-access areas. In this paper, we propose an effective transmission method for two-class sensed data for secure smart IoT systems. We divide the sensed data into two classes which consist of the urgent sensed data class (requiring urgent data transmission) and the normal sensed data class (with a slight transmission delay due to yielding to the urgent data transmission). In addition, for security reasons, the proposed transmission method uses two kinds of blockchains with the following two ledgers: (1) the urgent sensed data ledger, which is a ledger of data that needs urgent transmission; and (2) the normal sensed data ledger, which is a ledger of data that allows some delay. To be specific, the lightweight blockchain based on our earlier work is used for the normal sensed data transmission, whereas the modified conventional blockchain is used for the normal sensed data transmission. The experiments show that the performance of the proposed transmission method is better than the conventional transmission method in almost all sections. There is a 53% performance increase on average with regard to the transmission time. When the ratio of urgent sensed data is 0% (i.e., no urgent sensed data at all), the proposed transmission method is greater improved by as much as about 96%. This means that the lightweight blockchain scheme used in the proposed transmission method for the normal sensed data is very efficient. Full article
(This article belongs to the Special Issue Internet of Things, Smart Sensing and Data Fusion in Smart City)
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17 pages, 751 KiB  
Article
Robust Intra-Body Communication Using SHA1-CRC Inversion-Based Protection and Error Correction for Securing Electronic Authentication
by Seongho Cho and Daejin Park
Sensors 2020, 20(21), 6056; https://doi.org/10.3390/s20216056 - 24 Oct 2020
Cited by 3 | Viewed by 1848
Abstract
The explosive increase in the number of IoT devices requires various types of communication methods. This paper presents secure personal authentication using electrostatic coupling Intra-body communication (IBC) based on frequency shift keying (FSK) and error correction. The proposed architecture uses GPIO for a [...] Read more.
The explosive increase in the number of IoT devices requires various types of communication methods. This paper presents secure personal authentication using electrostatic coupling Intra-body communication (IBC) based on frequency shift keying (FSK) and error correction. The proposed architecture uses GPIO for a transmitter and analog-to-digital conversion (ADC) for a receiver. We mplemented FSK modulation, demodulation, data protection, and error correction techniques in the MCU software without applying hardware devices. We used the characteristic that the carrier signal is 50% duty square wave for 1-bit error correction and applied a method of randomly inverting SHA1 hash data to protect user authentication data during transmission. The transmitter modulates binary data using a square wave as a carrier signal and transmits data through the human body. The receiver demodulates the signal using ADC and decrypts the demodulated binary data. To determine the carrier frequency from ADC results, we applied a zero-crossing algorithm which is used to detect edge characteristics in image processing. When calculating the threshold value within the zero-crossing algorithm, we implemented an adaptive threshold setting technique utilizing Otsu’s binarization technique. We found that the size of the electrode pad does not affect the signal strength, but the distance between the electrode pad and the skin has a significant effect on the signal strength. Our results show that binary data modulated with a square wave can be successfully transmitted through the human body, and, when 1-bit error correction is applied, the byte error rate on the receiver side is improved around 3.5% compared to not applying it. Full article
(This article belongs to the Special Issue Internet of Things, Smart Sensing and Data Fusion in Smart City)
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