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Correction: Local densities and habitat preference of the critically endangered spotted handfish (Brachionichthys hirsutus): Large scale field trial of GPS parameterised underwater visual census and diver attached camera
[This corrects the article DOI: 10.1371/journal.pone.0201518.].
Journal Article
Recent Advances, Future Trends, Applications and Challenges of Internet of Underwater Things (IoUT): A Comprehensive Review
Oceans cover more than 70% of the Earth’s surface. For various reasons, almost 95% of these areas remain unexplored. Underwater wireless communication (UWC) has widespread applications, including real-time aquatic data collection, naval surveillance, natural disaster prevention, archaeological expeditions, oil and gas exploration, shipwreck exploration, maritime security, and the monitoring of aquatic species and water contamination. The promising concept of the Internet of Underwater Things (IoUT) is having a great influence in several areas, for example, in small research facilities and average-sized harbors, as well as in huge unexplored areas of ocean. The IoUT has emerged as an innovative technology with the potential to develop a smart ocean. The IoUT framework integrates different underwater communication techniques such as optical, magnetic induction, and acoustic signals. It is capable of revolutionizing industrial projects, scientific research, and business. The key enabler technology for the IoUT is the underwater wireless sensor network (UWSN); however, at present, this is characterized by limitations in reliability, long propagation delays, high energy consumption, a dynamic topology, and limited bandwidth. This study examines the literature to identify potential challenges and risks, as well as mitigating solutions, associated with the IoUT. Our findings reveal that the key contributing elements to the challenges facing the IoUT are underwater communications, energy storage, latency, mobility, a lack of standardization, transmission media, transmission range, and energy constraints. Furthermore, we discuss several IoUT applications while highlighting potential future research directions.
Journal Article
A history of the world in twelve shipwrecks
\"From renowned underwater archaeologist David Gibbins comes an exciting and rich narrative of human history told through the archaeological discoveries of twelve shipwrecks across time. The Viking warship of King Cnut the Great. Henry VIII's the Mary Rose. Captain John Franklin's doomed HMS Terror. The SS Gairsoppa, destroyed by a Nazi U-boat in the Atlantic during World War II. Since we first set sail on the open sea, ships and their wrecks have been an inevitable part of human history. Archaeologists have made spectacular discoveries excavating these sunken ships, their protective underwater cocoon keeping evidence of past civilizations preserved. Now, for the first time, world renowned maritime archeologist David Gibbins ties together the stories of some of the most significant shipwrecks in time to form a single overarching narrative of world history. A History of the World in Twelve Shipwrecks is not just the story of those ships, the people who sailed on them, and the cargo and treasure they carried, but also the story of the spread of people, religion, and ideas around the world; it is a story of colonialism, migration, and the indominable human spirit that continues today. From the glittering Bronze Age, to the world of Caesar's Rome, through the era of the Vikings, to the exploration of the Arctic, Gibbins uses shipwrecks to tell all. Drawing on decades of experience excavating shipwrecks around the world, Gibbins reveals the riches beneath the waves and shows us how the treasures found there can be a porthole to the past that tell a new story about the world and its underwater secrets\"-- Provided by publisher.
Book
Internet of Underwater Things: A Survey on Simulation Tools and 5G-Based Underwater Networks
The term “Internet of Underwater Things (IoUT)” refers to a network of intelligent interconnected underwater devices designed to monitor various underwater activities. The IoUT allows for a network of autonomous underwater vehicles (AUVs) to communicate with each other, sense their surroundings, collect data, and transmit them to control centers on the surface at typical Internet speeds. These data serve as a valuable resource for various tasks, including conducting crash surveys, discovering shipwrecks, detecting early signs of tsunamis, monitoring animal health, obtaining real-time aquatic information, and conducting archaeological expeditions. This paper introduces an additional set of alternative simulation tools for underwater networks. We categorize these tools into open-source and licensed simulator options and recommend that students consider using open-source simulators for monitoring underwater networks. There has not been widespread deployment or extensive research on underwater 5G-based networks. However, simulation tools provide some general insights into the challenges and potential issues associated with evaluating such networks, based on the characteristics of underwater communication and 5G, by surveying 5G-based underwater networks and 5G key aspects addressed by the research community in underwater network systems. Through an extensive review of the literature, we discuss the architecture of both Internet of Underwater application-assisted AUVs and Internet of Underwater Things communications in the 5G-based system.
Journal Article
Shipwrecked! : Diving for hidden time capsules on the ocean floor
\"Shipwrecked! is an adventure-filled nonfiction book for young readers about the most captivating shipwrecks from history. Combining new research, stunning archival material, and vivid storytelling, Shipwrecked! dives deep into the world of marine archaeology and shows young readers what each discovery reveals about the world before our time\"-- Provided by publisher.
Book
Survey on Low-Cost Underwater Sensor Networks: From Niche Applications to Everyday Use
Traditionally, underwater acoustic modems and positioning systems were developed for military and Oil & Gas industries, that require deep water deployments and extremely reliable systems, focusing on high power expensive systems and leaving the use of low-cost devices only attractive for academic studies. Conversely, recent developments of low-cost unmanned vehicles, such as remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs), suitable for shallow water coastal missions, and the need of sensors network deployments for measuring water quality and studying the effect of climate change in coastal areas, called to the need of low-cost and low-power acoustic modems and positioning systems that are gaining more and more momentum to date. The use of these devices can enable a wide set of applications, often based on low-cost AUV swarm formations, where an acoustic link between the vehicles is required to coordinate the mission, perform the maneuvers, and maintain the formation along the time. Moreover, they can make environmental wireless sensor deployment cost effective by substituting wired systems. Underwater positioning systems, usually used in large-scale operations, can be finally applied to small-scale application thanks to the reduction in costs, at the price of a lower transmission and positioning range and precision. While in open-sea application this performance reduction is a huge limitation, in river, lagoon, port and lake deployments this is not an issue, given that the extremely shallow water and the presence of many obstacles would deteriorate the acoustic signal anyway, not allowing long range transmissions even with expensive and sophisticated acoustic devices. In this paper, we review the recent developments of low-cost and low-power acoustic communication and positioning systems, both analyzing University prototypes and new commercial devices available in the market, identifying advantages and limitations of these devices, and we describe potential new applications that can be enabled by these systems.
Journal Article
Light and photosynthesis in aquatic ecosystems
\"Beginning systematically with the fundamentals, the fully-updated third edition of this popular graduate textbook provides an understanding of all the essential elements of marine optics. It explains the key role of light as a major factor in determining the operation and biological composition of aquatic ecosystems, and its scope ranges from the physics of light transmission within water, through the biochemistry and physiology of aquatic photosynthesis, to the ecological relationships that depend on the underwater light climate. This book also provides a valuable introduction to the remote sensing of the ocean from space, which is now recognized to be of great environmental significance due to its direct relevance to global warming. An important resource for graduate courses on marine optics, aquatic photosynthesis, or ocean remote sensing; and for aquatic scientists, both oceanographers and limnologists\"-- Provided by publisher.
Book
Underwater Image Restoration via Contrastive Learning and a Real-World Dataset
Underwater image restoration is of significant importance in unveiling the underwater world. Numerous techniques and algorithms have been developed in recent decades. However, due to fundamental difficulties associated with imaging/sensing, lighting, and refractive geometric distortions in capturing clear underwater images, no comprehensive evaluations have been conducted with regard to underwater image restoration. To address this gap, we constructed a large-scale real underwater image dataset, dubbed Heron Island Coral Reef Dataset (‘HICRD’), for the purpose of benchmarking existing methods and supporting the development of new deep-learning based methods. We employed an accurate water parameter (diffuse attenuation coefficient) to generate the reference images. There are 2000 reference restored images and 6003 original underwater images in the unpaired training set. Furthermore, we present a novel method for underwater image restoration based on an unsupervised image-to-image translation framework. Our proposed method leveraged contrastive learning and generative adversarial networks to maximize the mutual information between raw and restored images. Extensive experiments with comparisons to recent approaches further demonstrate the superiority of our proposed method. Our code and dataset are both publicly available.
Journal Article