Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/19449
Title: | Internet of Ships: A Survey on Architectures, Emerging Applications, and Challenges | Authors: | Aslam, Sheraz Michaelides, Michalis P. Herodotou, Herodotos |
Major Field of Science: | Natural Sciences | Field Category: | Computer and Information Sciences | Keywords: | Marine vehicles;Internet of Things;Industries;Transportation;Safety;Satellite communication;E-navigation;Internet of Ships (IoS);Internet of Things (IoT);Maritime industry;Sea transportation;Smart ocean;Smart ports;Smart shipping;Smart transportation | Issue Date: | Oct-2020 | Source: | IEEE Internet of Things Journal, 2020, vol. 7, no. 10, pp. 9714-9727 | Volume: | 7 | Issue: | 10 | Start page: | 9714 | End page: | 9727 | Journal: | IEEE Internet of Things Journal | Abstract: | The recent emergence of Internet-of-Things (IoT) technologies in mission-critical applications in the maritime industry has led to the introduction of the Internet-of-Ships (IoS) paradigm. IoS is a novel application domain of IoT that refers to the network of smart interconnected maritime objects, which can be any physical device or infrastructure associated with a ship, a port, or the transportation itself, with the goal of significantly boosting the shipping industry toward improved safety, efficiency, and environmental sustainability. In this article, we provide a comprehensive survey of the IoS paradigm, its architecture, its key elements, and its main characteristics. Furthermore, we review the state of the art for its emerging applications, including safety enhancements, route planning and optimization, collaborative decision making, automatic fault detection and preemptive maintenance, cargo tracking, environmental monitoring, energy-efficient operations, and automatic berthing. Finally, the presented open challenges and future opportunities for research in the areas of satellite communications, security, privacy, maritime data collection, data management, and analytics, provide a road map toward optimized maritime operations and autonomous shipping. | URI: | https://hdl.handle.net/20.500.14279/19449 | ISSN: | 23274662 | DOI: | 10.1109/JIOT.2020.2993411 | Rights: | © IEEE Attribution-NonCommercial-NoDerivatives 4.0 International |
Type: | Article | Affiliation : | Cyprus University of Technology | Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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