South Korean startup Seadronix wants to reduce the issue of marine accidents, 75% of which are caused by human error, according to a 2019 Allianz safety and shipping report. The company just secured a $5.8 million Series A extension to scale its AI-based ship berthing monitoring and navigation systems to help cargo ships navigate safely and assist port operators anchoring their vehicles at harbor. The fresh funds, led by SoftBank Ventures Asia, bring Seadronix's the total round up to $8.3 million. Seadronix will use the capital to grow its team beyond the current headcount of 30 employees and enter global markets, including Singapore and Europe, where its "smart ports" are located, Byeolteo Park, CEO and co-founder, said in an interview with TechCrunch. A smart port uses technologies including AI, big data, Internet of Things and 5G to provide more security and save energy by digitalizing the way huge ships enter docks and handle logistics at the ports.
On August 8th, 2021, Spanish police and customs agents intercepted the cargo ship NATALIA on suspicion of narcotics trafficking. The ship was en route from Lebanon via Iskenderun, Turkey to Lagos, Nigeria, and hidden on board was nearly 20 tons of hashish worth $470M. That may sound like the opening scene of an action flick, but it's the kind of occurrence that happens more frequently than you might expect on the high seas. Drug smuggling, illegal fishing, and piracy are constant threats. Following a number of recent piracy incidents in the Gulf of Aden, Iran, Russia, and China recently began naval and air drills seeking to counter maritime piracy.
FrontM is on a mission to be the EDGE-intelligent app marketplace where the world goes to connect, inform and care for remote teams and customers. The innovation focuses on overcoming digital poverty in remote and isolated environments, such as the Blue Economy. The World Bank defines the blue economy as the "sustainable use of ocean resources for economic growth, improved livelihoods and jobs while preserving the health of the ocean ecosystem." FrontM's initial use cases include the maritime commercial shipping market, particularly transforming shore-ship team collaboration, automation of workflows, crew safety and welfare. FrontM is proud to be recognised by Innovate UK and receiving a grant to study the feasibility of integration of Edge AI enablement technology from Hammer Of The Gods (HOT-G).
AutoML is a type of machine learning (ML) in which the tasks and processes for developing learning models for machines are automated rather than iteratively built by developers. As enterprises collect more data than any human could tackle, autoML helps by building ML models quickly and at scale. These tasks have become increasingly complex, and as more businesses adopt ML applications, the demand for ML experts and data scientists far outpaces enterprises' ability to hire them. Out-of-box autoML solutions, such as Auto-sklearn and Auto-PyTorch, have thus become more commonplace because autoML is more accessible to those with little or no coding experience. Since autoML automates tasks involved to optimize machine learning models and develop deep neural networks, this reduces the chance of error from human intervention.
As the technology improves all around us, the dependence of humans on machines has increased over time admirably. The term'Artificial Intelligence' or AI was adopted first in the year 1956 by John McCarthy, an American Computer Scientist at the Darthmouth Conference. Since then, Artificial Intelligence has evolved over the years such that today, there are infinite uses of Artificial Intelligence and Machine Learning from manufacturing sectors to academics, healthcare, telecommunication and Academics. Before Learning about Autonomous Shipping, let us learn about the basics or the fundamental pillars that autonomous shipping is based on. Artificial Intelligence (AI) is the simulation of human intelligence by machines.
Shipping is critical to our modern life. As goods criss-cross around the globe, demand is higher than ever. But there's also a push to make these logistics smarter and more eco friendly. AI can help with that. So, to that end, here's a quick guide to Artificial Intelligence in shipping and how AI can work for you.
Collision avoidance is a vital capability of any marine vessel navigating in public waterways; this is particularly true for autonomous surface vehicles (ASVs), which cannot benefit by the real-time guidance of a human operator. Safe maritime navigation remains a challenge due to the fact that it requires the seamless coordination of multiple complex subsystems. First, vessels must be able to perceive their surroundings under a wide range of environmental conditions. This is typically accomplished using one or more line-of-sight sensors, which emit electromagnetic or acoustic signals, and detect the reflections produced by nearby obstacles (Robinette et al., 2019). However, in the marine environment, vessels can also utilize the Automatic Information System (AIS) protocol to track nearby vessels. The merits and drawbacks of these sensing modalities will be discussed in Section 1.1. Once an obstacle is detected, the ASV must react quickly and intelligently to avoid it, in accordance with the "rules of the road" set forth by the 1972 International Regulations for Prevention of Collisions at Sea (COLREGs) (International Maritime Organization, 2003). Many ASVs remain unable to perform one or more of these crucial tasks, limiting their adoption beyond the oceanographic research community. B. Cole is with the Laboratory for Autonomous Marine Sensing Systems, Department of Mechanical Engineering.
The shipping industry is an important component of the global trade and economy, however in order to ensure law compliance and safety it needs to be monitored. In this paper, we present a novel Ship Type classification model that combines vessel transmitted data from the Automatic Identification System, with vessel imagery. The main components of our approach are the Faster R-CNN Deep Neural Network and a Neuro-Fuzzy system with IF-THEN rules. We evaluate our model using real world data and showcase the advantages of this combination while also compare it with other methods. Results show that our model can increase prediction scores by up to 15.4\% when compared with the next best model we considered, while also maintaining a level of explainability as opposed to common black box approaches.
Artificial intelligence could one day organize the world. As if in anticipation of this, a maritime platform developer called Orca AI has just begun a research trial of new safety systems for autonomous ships, equipping a vessel with artificial intelligence that recognizes other ships to safely guide it through busy sea traffic, according to a recent press release from the company. Orca AI was founded in 2018 by a pair of naval tech experts, and designs software platforms with extreme specificity for maritime vessels. The firm blends existing safety systems with sensors to enhance the navigation and safety of vessels making their way through crowded (and sometimes dangerous) waterways. Orca AI is headquartered in Israel, and aims to link sea-bound vessels with 24/7 land-based AI insights.
Israel's defense minister warned Thursday that his country is prepared to strike Iran, issuing the threat against the Islamic Republic after a fatal drone strike on a oil tanker at sea that his nation blamed on Tehran. The comments by Benny Gantz come as Israel lobbies countries for action at the United Nations over last week's attack on the oil tanker Mercer Street that killed two people. The tanker, struck off Oman in the Arabian Sea, is managed by a firm owned by an Israeli billionaire. The U.S. and the United Kingdom also blamed Iran for the attack, but no country has offered evidence or intelligence to support the claim. Iran, which along with its regional militia allies has launched similar drone attacks, has denied being involved.