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Intelligent Industrial Application of Consumer Wireless Technologies
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Intelligent Industrial Application of Consumer Wireless Technologies

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

Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 16476

Special Issue Editors

Prof. Dr. Gerhard P. Hancke

E-Mail Website1 Website2
Guest Editor
1. College of Automation and Artificial Intelligence, Nanjing University of Posts and Telecommunication, Nanjing, China
2. Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria, South Africa
Interests: wireless sensor networks
Dr. Mithun Mukherjee

E-Mail Website
Guest Editor
Guangdong University of Petrochemical Technology, China
Interests: wireless sensor network; wireless communications; energy harvesting; cloud computing

Special Issue Information

Dear Colleagues,

There are a number of new wireless technologies aimed primarily at connecting consumers and creating commercial networks, such as LoRa, Sigfox, LTE-M, and NB-IoT. These technologies can also be applied to existing and new industrial applications and Industrial Internet of Things (IIoT); however, this would require systems to ensure network performance, such as reliable connectivity and latency, appropriate intelligent information processing, in addition to device management. The main objective of this Special Issue is to provide a forum to share and discuss new ideas, use cases, and research results on all aspects of industrial wireless technologies. You are invited to submit original research contributions in all related areas, which include, but are not limited to:

  • Intelligent and innovative wireless industrial applications for consumers
  • Intelligent information processing for these application
  • Software-defined networking, network functions virtualization, and network slicing for IIoT
  • Edge, fog, and cloud computing for IIoT
  • Energy efficiency and energy harvesting for LoRa, Sigfox, LTE-M, and NB-IoT
  • Simulation, testbeds, prototypes, field trails, and other performance analyses
  • Channel characterisation and modelling in industrial environments
  • Wireless ranging, device localisation, and location-based services

Prof. Dr. Gerhard P. Hancke
Dr. Mithun Mukherjee
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
  • industrial IoT
  • localisation
  • embedded intelligence
  • narrow-band IoT

Published Papers (3 papers)

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Research

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25 pages, 3049 KiB  
Article
Behavioral Acoustic Emanations: Attack and Verification of PIN Entry Using Keypress Sounds
by Sourav Panda, Yuanzhen Liu, Gerhard Petrus Hancke and Umair Mujtaba Qureshi
Sensors 2020, 20(11), 3015; https://doi.org/10.3390/s20113015 (registering DOI) - 26 May 2020
Cited by 9 | Viewed by 4375
Abstract
This paper explores the security vulnerability of Personal Identification Number (PIN) or numeric passwords. Entry Device (PEDs) that use small strings of data (PINs, keys or passwords) as means of verifying the legitimacy of a user. Today, PEDs are commonly used by personnel [...] Read more.
This paper explores the security vulnerability of Personal Identification Number (PIN) or numeric passwords. Entry Device (PEDs) that use small strings of data (PINs, keys or passwords) as means of verifying the legitimacy of a user. Today, PEDs are commonly used by personnel in different industrial and consumer electronic applications, such as entry at security checkpoints, ATMs and customer kiosks, etc. In this paper, we propose a side-channel attack on a 4–6 digit random PIN key, and a PIN key user verification method. The intervals between two keystrokes are extracted from the acoustic emanation and used as features to train machine-learning models. The attack model has a 60% chance to recover the PIN key. The verification model has an 88% accuracy on identifying the user. Our attack methods can perform key recovery by using the acoustic side-channel at low cost. As a countermeasure, our verification method can improve the security of PIN entry devices. Full article
(This article belongs to the Special Issue Intelligent Industrial Application of Consumer Wireless Technologies)
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28 pages, 3672 KiB  
Article
Evaluating the Implications of Varying Bluetooth Low Energy (BLE) Transmission Power Levels on Wireless Indoor Localization Accuracy and Precision
by Umair Mujtaba Qureshi, Zuneera Umair and Gerhard Petrus Hancke
Sensors 2019, 19(15), 3282; https://doi.org/10.3390/s19153282 - 25 Jul 2019
Cited by 31 | Viewed by 4411
Abstract
Bluetooth Low Energy (BLE) based Wireless Indoor Localization System (WILS) with high localization accuracy and high localization precision is a key requirement in enabling the Internet of Things (IoT) in today’s applications. In this paper, we investigated the effect of BLE signal variations [...] Read more.
Bluetooth Low Energy (BLE) based Wireless Indoor Localization System (WILS) with high localization accuracy and high localization precision is a key requirement in enabling the Internet of Things (IoT) in today’s applications. In this paper, we investigated the effect of BLE signal variations on indoor localization caused by the change in BLE transmission power levels. This issue is not often discussed as most of the works on localization algorithms use the highest power levels but has important practical implications for energy efficiency, e.g., if a designer would like to trade-off localization performance and node lifetime. To analyze the impact, we used the established trilateration based localization model with two methods i.e., Centroid Approximation (CA) and Minimum Mean Square Error (MMSE). We observed that trilateration based localization with MMSE method outperforms the CA method. We further investigated the use of two filters i.e., Low Pass Filter (LPF) and Kalman Filter (KF) and evaluated their effects in terms of mitigating the random variations from BLE signal. In comparison to non-filter based approach, we observed a great improvement in localization accuracy and localization precision with a filter-based approach. Furthermore, in comparison to LPF based trilateration localization with CA, the performance of a KF based trilateration localization with MMSE is far better. An average of 1 m improvement in localization accuracy and approximately 50% improvement in localization precision is observed by using KF in trilateration based localization model with the MMSE method. In conclusion, with KF in trilateration based localization model with MMSE method effectively eliminates random variations in BLE RSS with multiple transmission power levels and thus results in a BLE based WILS with high accuracy and high precision. Full article
(This article belongs to the Special Issue Intelligent Industrial Application of Consumer Wireless Technologies)
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Review

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25 pages, 961 KiB  
Review
A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges
by Rachel Kufakunesu, Gerhard P. Hancke and Adnan M. Abu-Mahfouz
Sensors 2020, 20(18), 5044; https://doi.org/10.3390/s20185044 - 5 Sep 2020
Cited by 111 | Viewed by 7305
Abstract
Long-Range Wide Area Network (LoRaWAN) is a fast-growing communication system for Low Power Wide Area Networks (LPWAN) in the Internet of Things (IoTs) deployments. LoRaWAN is built to optimize LPWANs for battery lifetime, capacity, range, and cost. LoRaWAN employs an Adaptive Data Rate [...] Read more.
Long-Range Wide Area Network (LoRaWAN) is a fast-growing communication system for Low Power Wide Area Networks (LPWAN) in the Internet of Things (IoTs) deployments. LoRaWAN is built to optimize LPWANs for battery lifetime, capacity, range, and cost. LoRaWAN employs an Adaptive Data Rate (ADR) scheme that dynamically optimizes data rate, airtime, and energy consumption. The major challenge in LoRaWAN is that the LoRa specification does not state how the network server must command end nodes pertaining rate adaptation. As a result, numerous ADR schemes have been proposed to cater for the many applications of IoT technology, the quality of service requirements, different metrics, and radio frequency (RF) conditions. This offers a challenge for the reliability and suitability of these schemes. This paper presents a comprehensive review of the research on ADR algorithms for LoRaWAN technology. First, we provide an overview of LoRaWAN network performance that has been explored and documented in the literature and then focus on recent solutions for ADR as an optimization approach to improve throughput, energy efficiency and scalability. We then distinguish the approaches used, highlight their strengths and drawbacks, and provide a comparison of these approaches. Finally, we identify some research gaps and future directions. Full article
(This article belongs to the Special Issue Intelligent Industrial Application of Consumer Wireless Technologies)
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