The NEPTUNE Canada Communications Network

Lentz, S.

doi:10.1109/oceans.2007.4449150

Cited by 4 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach uses the VHF radio solution of the Automatic Identification System (AIS) for conveying data packets [42]. It is worth noting that wired protocols -such as the IEEE 802.3 for LAN (Ethernet) -can still be employed in IoUT projects after modest reconfiguration [78].…”

Section: ) Physical Layer In Ioutmentioning

confidence: 99%

Internet of Underwater Things and Big Marine Data Analytics—A Comprehensive Survey

Jahanbakht

Wang

Hanzo

et al. 2021

IEEE Commun. Surv. Tutorials

263

111

View full text Add to dashboard Cite

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed. Accordingly, the reader will become familiar with the pivotal issues of IoUT and BMD processing, whilst gaining an insight into the state-of-theart applications, tools, and techniques. Finally, we analyze of the architectural challenges of the IoUT, followed by proposing a range of promising direction for research and innovation in the broad areas of IoUT and BMD. Our hope is to inspire researchers, engineers, data scientists, and governmental bodies to further progress the field, to develop new tools and techniques, as well as to make informed decisions and set regulations related to the maritime and underwater environments around the world.

show abstract

Section: ) Physical Layer In Ioutmentioning

confidence: 99%

Internet of Underwater Things and Big Marine Data Analytics—A Comprehensive Survey

Jahanbakht

Wang

Hanzo

et al. 2021

IEEE Commun. Surv. Tutorials

263

111

View full text Add to dashboard Cite

show abstract

“…Seafloor observatory network adopts the single-stage medium-voltage DC parallel transmission mode and Dense Wavelength Division Multiplexing (DWDM) technology (Figure 1) [4][5]. It has important practical significance to explore how to separate the submarine cable fault in the parallel mode and distinguish the separate and coupling of different wavelength in space.…”

Section: Introuctionmentioning

confidence: 99%

“…Seafloor observatory network has broken the constraints of energy and data transmission, and makes that it is possible to obtain long-term, real-time, large range, large amount data observation of the seafloor. Seafloor observatory network adopts the single-stage medium-voltage DC parallel transmission mode and Dense Wavelength Division Multiplexing (DWDM) technology (Figure 1) [4][5]. It has important practical significance to explore how to separate the submarine cable fault in the parallel mode and distinguish the separate and coupling of different wavelength in space.…”

Section: Introuctionmentioning

confidence: 99%

Branch Unit for Seafloor Observatory Network

Feng

Wang

2013

AMR

View full text Add to dashboard Cite

Abstract. One key issue of seafloor observatory network is to ensure that the whole system operates normally when some equipment failure exists. Branch Unit can cut off the connection between the failure parts and the backbone network automatically and protect other equipment of the network from the impact of equipment failure. This paper proposes a design of the Branch Unit. The Branch Unit uses zener diode to provide power for the control circuits and constructs DWDM system with the help of the OADM. One Branch Unit model was built in this paper. Experiments verify the principle and functions of the Branch Unit and prove the feasibility of the design. The design provides a reference for the realization of the seafloor observatory network. IntrouctionOceans cover 70 percent of the earth's surface; the seafloor is rich in natural resources such as manganese nodules, hydrothermal sulfide, oil and gas, and natural gas hydrate. Exploration and exploitation of marine resources is very important for human survival and sustainable development [1]. Following the ground/ocean and space, seafloor observatory network becomes the third platform of observing the earth system. The North Eastern Pacific Time-Series Undersea Networked Experiment (NEPTUNE) and ESONET are two sub-sea networks, which were initiated by the USA and Canada (NEPTUNE) and European Union respectively [2][3]. Seafloor observatory network is gradually becoming a new hot spot in the field of marine science and technology. Compared with foreign countries, seafloor observatory network construction starts relatively late in China. But some important progress in some key technology has yet been made.Seafloor observatory network has broken the constraints of energy and data transmission, and makes that it is possible to obtain long-term, real-time, large range, large amount data observation of the seafloor. Seafloor observatory network adopts the single-stage medium-voltage DC parallel transmission mode and Dense Wavelength Division Multiplexing (DWDM) technology (Figure 1) [4][5]. It has important practical significance to explore how to separate the submarine cable fault in the parallel mode and distinguish the separate and coupling of different wavelength in space.

show abstract

“…These observatories are cabled networks designed to include many types of instrumentation and carry large amounts of data. For example, Neptune Canada [6], [7] has a backbone cable that carries both power and fiber-optic bidirectional communications across the network with repeaters that amplify the optical signal carrying information. The backbone contains branching units to distribute power and communications to spur cables connecting network nodes.…”

Section: Introduction Ocean Acoustic Tomography (Oat) Is a Remote mentioning

confidence: 99%

Acoustic observatories for ocean tomography: Multi-array matched-field tomography

Soares

Felisberto

Jesus

2011

OCEANS 2011 IEEE - Spain

View full text Add to dashboard Cite

Abstract-The present study proposes an MFT algorithm for directly estimating a two-dimensional range-dependent or three-dimensional temperature field. The acoustic system has multiple acoustic emitters and receiver arrays according to a given geometry. The acoustic signal is emitted from one emitter at a time, and collected at multiple receiver arrays. The MFT method is adapted to iteratively produce parameter estimates for each individual environmental cell. To accomplish this, an MF processor based on a multi-array acoustic data model is considered, in order to account for acoustic data collected simultaneously at several acoustic arrays.

show abstract

The NEPTUNE Canada Communications Network

Cited by 4 publications

References 0 publications

Internet of Underwater Things and Big Marine Data Analytics—A Comprehensive Survey

Internet of Underwater Things and Big Marine Data Analytics—A Comprehensive Survey

Branch Unit for Seafloor Observatory Network

Acoustic observatories for ocean tomography: Multi-array matched-field tomography

Contact Info

Product

Resources

About