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Silverstream Wins Innovate UK KTP Grant To Advance Machine Learning In Maritime

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Silverstream Technologies, the leading air lubrication manufacturer for the shipping industry, in collaboration with the University of Southampton, has been awarded an Innovate UK Knowledge Transfer Partnership (KTP) grant to advance machine learning in the maritime sector, the organisations have announced today. The two-year partnership will see an Associate of the University of Southampton, secured under the programme, work with Silverstream's Technical Team with the goal to advance machine learning and artificial intelligence within the Silverstream System's control and automation module. The Silverstream System uses air lubrication to reduce frictional resistance between a vessel's hull and the water and delivers fuel savings of 5-10% depending on the vessel and its operating profile. The KTP will aim to increase this saving by analysing operational data taken from installed systems. This data, when combined with cutting edge machine learning techniques, will help to further increase Silverstream System performance during a voyage, with the goal of gaining the theoretical maximum savings associated with the technology every time it is operating.


British treasure finders accused of piracy

Daily Mail - Science & tech

British archaeologists who discovered hundreds of artefacts from a cluster of 17th century shipwrecks in the Mediterranean Sea have had their cargo seized and been accused of an'illicit excavation'. Enigma Recoveries, which led an expedition into the Levantine Basin off the coast of Cyprus, found 12 shipwrecks filled with Chinese porcelain, jugs, coffee pots, peppercorns and illicit tobacco pipes. The ships and their priceless cargo, hailed as the'archaeological equivalent of finding a new planet' were recovered in ancient'shipping lanes' that served spice and silk trades from 300 BC onwards. But in a strongly-worded statement, the Cypriot government accused the company of being well known to both Cyprus and UNESCO for its'illicit underwater excavations' and its'violent extraction of objects causing destruction to their context'. Cyprus's Department of Antiquities accused the company of intending to sell the objects, as allegedly evident in documents filed with the United States Securities and Exchange Commission (NASDAQ).


12 shipwrecks uncovered in the east Med dating from 300 BC

Daily Mail - Science & tech

Archaeologists have found shipwrecks in the Mediterranean filled with hundreds of artefacts including Chinese porcelain, jugs, coffee pots, peppercorns and illicit tobacco pipes. A British-led expedition found a cluster of 12 ships on the sea bed, 1.2 miles below the surface of the Levantine Sea, using sophisticated robots. The ships were recovered in ancient'shipping lanes' that served spice and silk trades of the Greek, Roman and Ottoman empires, from 300 BC onwards. The ancient ships – including the biggest ever found in the Med – were unearthed in a muddy part of the eastern seabed between Cyprus and Lebanon, where remnants are often hard to find. The cluster of shipwrecks were found in the Levantine Basin in the east of the Mediterranean Sea.


Fully Autonomous Ship Starts Trials Ahead of Trans-Atlantic Crossing

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Plans to recreate the 1620 trans-Atlantic journey of the Mayflower colony ship with a fully autonomous, crewless vessel are one step closer, as IBM begins trials of the ship's AI "captain" in a project that could set the scene for future crewless cargo shipping. The Mayflower Autonomous Ship (MAS) project undertaken by IBM, the University of Plymouth and marine research firm ProMare aims to create the world's first fully-sized autonomous research vessel that will cross the Atlantic this September. For the last two years an AI model has been trained using a million nautical images collected from open source data sets. In order to process this database, a team in Plymouth are using an IBM Power AC922 server fitted with Nvidia V100 Tensor Core GPUs. Upon completion the ship itself will be fitted with an IBM Power System accelerated server that will be tasked with helping the AI captain act independently on the high seas.


Real-Time target detection in maritime scenarios based on YOLOv3 model

arXiv.org Machine Learning

In this work a novel ships dataset is proposed consisting of more than 56k images of marine vessels collected by means of web-scraping and including 12 ship categories. A YOLOv3 single-stage detector based on Keras API is built on top of this dataset. Current results on four categories (cargo ship, naval ship, oil ship and tug ship) show Average Precision up to 96% for Intersection over Union (IoU) of 0.5 and satisfactory detection performances up to IoU of 0.8. A Data Analytics GUI service based on QT framework and Darknet-53 engine is also implemented in order to simplify the deployment process and analyse massive amount of images even for people without Data Science expertise.


Oceans of opportunity: surveying 2020's seafaring startup potential – TechCrunch

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Space attracts a lot of attention as an area of frontier tech investment and entrepreneurship, but there's another vast expanse that could actually be more addressable by the innovation economy -- Earth's oceans. Seafaring startups aren't attracting quite as much attention as their spacefaring cousins, but 2019 still saw a flurry of activity in this sector and 2020 could be an even big year for everything aquatic. One big similarity between space tech and seafaring opportunities is that data collection represents a significant percent of the potential market. Data collection in and around Earth's oceans has increased dramatically in recent years thanks to the availability, efficacy and cost of sensor technologies -- in 2017, it was estimated that as much ocean data had been gathered in the past two years as in all of human history. Ocean observation has largely been driven by scientific and research goals, which means there's bound to be a pretty hard cap on available funding.


Modeling Historical AIS Data For Vessel Path Prediction: A Comprehensive Treatment

arXiv.org Artificial Intelligence

The prosperity of artificial intelligence has aroused intensive interests in intelligent/autonomous navigation, in which path prediction is a key functionality for decision supports, e.g. route planning, collision warning, and traffic regulation. For maritime intelligence, Automatic Identification System (AIS) plays an important role because it recently has been made compulsory for large international commercial vessels and is able to provide nearly real-time information of the vessel. Therefore AIS data based vessel path prediction is a promising way in future maritime intelligence. However, real-world AIS data collected online are just highly irregular trajectory segments (AIS message sequences) from different types of vessels and geographical regions, with possibly very low data quality. So even there are some works studying how to build a path prediction model using historical AIS data, but still, it is a very challenging problem. In this paper, we propose a comprehensive framework to model massive historical AIS trajectory segments for accurate vessel path prediction. Experimental comparisons with existing popular methods are made to validate the proposed approach and results show that our approach could outperform the baseline methods by a wide margin.


Anybody Aboard?

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Artificial intelligence will soon be making a career in the maritime industry: Because specialist personnel and cargo space are scarce and transport costs are high, more and more ship owners are relying on ships with state-of-the-art assistance systems and autonomous driving functions. Autonomous ships will get by completely without captain and crew. When autonomous vessels plough through the waves in the future, the history of ghost ships will have to be rewritten. Legends like the Flying Dutchman and the Marie Celeste have one thing in common. Both vessels had a crew on board before fate befell them in the vastness of the oceans.


Best Artificial Intelligence Logistics Startups -- Transmetrics Blog

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This article about the best artificial intelligence logistics startups is part of the "Logistics of the Future" series looking at the top logistics startups today. We are officially living in the age of Artificial Intelligence. It's everywhere we look, from AI-powered personal assistants to predictive analytics to making medical diagnoses, Artificial Intelligence is making incredible advances across all industries. In fact, a recent report on the state of Artificial Intelligence for enterprises found that supply chain and operations are some of the top areas where businesses are driving revenue from AI investment. Why is AI making such a big difference in the logistics and supply chain, particularly?


Tech may be taking away jobs, but it is creating many more of them: ULCC Group CEO Raveendran Kasthuri

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There is no need to raise an alarm over loss of jobs from induction of existing technology, because even more jobs are being created in its wake, says Raveendran Kasthuri, ex-IBMer and Group CEO of the Uralungal Labour Contract Cooperative Society (ULCC), based in Kozhikode, Kerala. Started as a cooperative society by labourers, ULCC has now grown to become one of the largest workers' cooperatives in Asia, at a time when, back home, cooperatives have come under the regulatory scanner for many reasons. As Group CEO, Kasthuri also looks after UL technology Solutions (ULTS), which was established in 2011 to maintain a balance between traditional and modern technologies. It offers a unique mix of traditional values and modern technological insights in its services and helps to formulate and implement comprehensive solutions for clients. ULTS describes itself as a cooperative corporate, with a focus on technology verticals such as Geographic Information System (GIS), Enterprise Resource Planning (ERP), Internet of Things (IoT), Blockchain, Artificial Intelligence (AI) and analytics.