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Special Issue "Internet of Underwater Things"

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

Deadline for manuscript submissions: 30 November 2020.

Special Issue Editors

Prof. Dr. Dongkyun Kim
Guest Editor
School of Computer Science and Engineering, Kyungpook National University, Daegu 41566, Korea
Interests: connected cars; vehicular ad hoc networks; the Internet of Things (machine-to-machine/device-to-device); Wi-Fi networks (including Wi-Fi Direct); wireless mesh networks; wireless sensor networks; future Internet
Special Issues and Collections in MDPI journals
Prof. Dr. Juan-Carlos Cano
Website SciProfiles
Guest Editor
Department of Computer Engineering, Universitat Politècnica de València, 46022 Valencia, Spain
Interests: wireless networks; Intelligent Transport Systems (ITS); design, modeling, and implementation of computer networks; power aware routing protocols; quality of service for mobile ad hoc networks; pervasive computing; protocols for Unmanned Aerial Vehicles
Special Issues and Collections in MDPI journals
Dr. Wei Wang
Guest Editor
Department of Computer Science, College of Sciences, San Diego State University, San Diego, CA 92182-7720, USA
Interests: wireless networks; wireless multimedia communications; QoE–QoS issues; network economics; IoTs
Dr. Syed Hassan Ahmed
Guest Editor
JMA Wireless, USA
Interests: Vehicular communications (routing, MAC); next generation networks (information/content-centric and named data networking); Internet of Things (IoT); connected and smart communities; sensors and ad hoc networks; smart and mobile health
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

From wired sensor nodes sensing, collecting, and forwarding data underwater, technology has evolved tremendously. In the past few decades, more feasible underwater communication solutions have been introduced, including wireless underwater sensor nodes. These sensor nodes have the capability to communicate underwater via high-frequency signals, acoustic signals, or light signals based on application-specific requirements. The introduction of autonomous robots with sensing and reporting capabilities that have the capability to dive deep within underwater environments has further enhanced the capacity for underwater environment monitoring. Small autonomous submarines equipped with underwater sensing capabilities, commonly known as autonomous underwater vehicles (AUVs), can communicate and cooperate within a group of AUVs to expand underwater operational capabilities.

Underwater sensing nodes communicate and forward data to the control station, forming the application-specific network of things. These networks of underwater things share resources and interact with other networks forming the Internet of Underwater Things (IoUT). The applications of IoUT include surveillance, oil and gas exploration, tectonic plate monitoring, and marine life and coral reef harvesting. The introduction of artificial intelligence into underwater communication further expands and improves upon the efficiency of underwater communication technologies due to its self-sustainable nature along with self-governance and independent decision making.

Several artificial intelligence (AI) problem-solving algorithms have been proposed, and most of them are still are at early stages, improving and evolving with time. These algorithms have the capability to process huge amounts of data and make intelligent decisions independently. In the absence of intelligence, IoUT systems will operate on a conventional communication system with preset rules of business. In future, the huge number of IoUT devices and massive traffic from these devices means only one thing—a massive amount of data arriving from stationary nodes as well as mobile AUVs. Numerical analysis techniques and state-of-the-art optimization algorithms can also result in intelligence of some level for the IoUT communication system as they can enhance the system performance.

Considering the importance of intelligent AUV in the internet of underwater things and the massive amounts of data generated from the communication system, this Special Issue seeks to collect relevant and original research and review articles to advance the field and encourage researchers. We welcome contributions from both the industry and academia in highlighting and introducing solutions to the challenges associated with the internet of underwater things systems.

Potential topics include but are not limited to the following:

  • Intelligent green underwater vehicular communication;
  • Security and privacy for underwater vehicular communication;
  • Intelligent internet of Autonomous Underwater Vehicles (AUVs);
  • Intelligent applications of the IoUT;
  • Underwater localization and tracking;
  • Big data/data mining for underwater vehicular communication;
  • Protocols and standards of intelligent underwater vehicular communication;
  • Intelligent IoUT solutions for smart eHealth of marine life monitoring.

Prof. Dr. Dongkyun Kim
Prof. Dr. Juan-Carlos Cano
Dr. Wei Wang
Dr. Syed Hassan Ahmed
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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 papers will be 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 2000 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.

Published Papers (1 paper)

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Open AccessArticle
Underwater Localization via Wideband Direction-of-Arrival Estimation Using Acoustic Arrays of Arbitrary Shape
Sensors 2020, 20(14), 3862; - 10 Jul 2020
Underwater sensing and remote telemetry tasks necessitate the accurate geo-location of sensor data series, which often requires underwater acoustic arrays. These are ensembles of hydrophones that can be jointly operated in order to, e.g., direct acoustic energy towards a given direction, or to [...] Read more.
Underwater sensing and remote telemetry tasks necessitate the accurate geo-location of sensor data series, which often requires underwater acoustic arrays. These are ensembles of hydrophones that can be jointly operated in order to, e.g., direct acoustic energy towards a given direction, or to estimate the direction of arrival of a desired signal. When the available equipment does not provide the required level of accuracy, it may be convenient to merge multiple transceivers into a larger acoustic array, in order to achieve better processing performance. In this paper, we name such a structure an “array of opportunity” to signify the often inevitable sub-optimality of the resulting array design, e.g., a distance between nearest array elements larger than half the shortest acoustic wavelength that the array would receive. The most immediate consequence is that arrays of opportunity may be affected by spatial ambiguity, and may require additional processing to avoid large errors in wideband direction of arrival (DoA) estimation, especially as opposed to narrowband processing. We consider the design of practical algorithms to achieve accurate detections, DoA estimates, and position estimates using wideband arrays of opportunity. For this purpose, we rely jointly on DoA and rough multilateration estimates to eliminate spatial ambiguities arising from the array layout. By means of emulations that realistically reproduce underwater noise and acoustic clutter, we show that our algorithm yields accurate DoA and location estimates, and in some cases it allows arrays of opportunity to outperform properly designed arrays. For example, at a signal-to-noise ratio of –20 dB, a 15-element array of opportunity achieves lower average and median localization error (27 m and 12 m, respectively) than a 30-element array with proper λ / 2 element spacing (33 m and 15 m, respectively). We confirm the good accuracy of our approach via emulation results, and through a proof-of-concept lake experiment, where our algorithm applied to a 10-element array of opportunity achieves a 90th-percentile DoA estimation error of 4 and a 90th-percentile total location error of 5 m when applied to a real 10-element array of opportunity. Full article
(This article belongs to the Special Issue Internet of Underwater Things)
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