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Artificial Intelligence

Shipowners Still Not Ready to Give Up Control to Autonomous Vessels

Shipowners seem to be hesitant to relinquish control of their vessels in favor of autonomous solutions, as they trust their captains and crews more than smart technology.

In general, the shipping industry’s approach to new technologies has been described as “conservative“, especially when it comes to autonomous solutions that could theoretically replace the crew.

This has led to the slow adoption of solutions that are vital to reducing collisions, Yarden Gross, CEO of Orca AI revealed in an interview with World Maritime News.

In order to overcome the maritime industry’s fear of new technology adoption, the company has designed the Orca AI system to be “a tool that the crews can use, not to replace the crew.”

Established in 2018, Orca AI has the vision to reduce human-caused errors through intelligent autonomous vessels. The company was founded by Yarden Gross and Dor Raviv, who both have served in the navy and know the industry and its needs.

“We realized that despite the technological advances being adopted for other modes of transport, the shipping industry is lagging behind. This is due to a variety of factors, including that the maritime environment requires navigation and collision avoidance technology, which need to be specifically suited to the industry and that’s what we seek to provide,” Gross said.

“We want to help create an ecosystem that will lead us to autonomous ships while keeping in mind that we’re not quite there yet.”

He added that there are things that need to be done to improve safety now — providing collision avoidance technology that works for ships.

As informed, 3,000 marine collisions occur each year and more than 75% are due to errors in human judgment. According to Gross, this is alarming as current navigational tools require a significant reliance on human judgment, which leaves room for costly error.

“Our immediate goal was to create a solution that would help ships use AI safely navigate zero and extremely low visibility conditions and crowded waterways, where the majority of collisions take place. Our solution minimizes the opportunity for errors in judgment, thereby reducing the chances of collisions.”

Orca AI system

Specifically, the Orca AI system uses sensors already on board a vessel and adds separate ones as well, such as thermal and low-light cameras, and feeds the information into an AI-powered navigation system.

The system was designed to be easy to use and intuitive, given that the crew manning the bridge is occupied with a myriad of responsibilities, so the system enables them to make smarter navigation decisions more easily. There is no training required to operate the system and it doesn’t add extra work for the crew, Yarden said.

As visibility issues are common and a big contributing factor in naval collisions, Orca AI founders said they decided to tackle that issue right from the start with sensors designed for situations with poor visibility. Orca AI is currently operational and providing crews with crucial information in piloted installations on board vessels. Those pilots are continuing as the company develops new versions of the system.

Installation

Orca AI has been installed and piloted onboard several car carriers owned by Ray Carriers, the company’s first client and key investor.

Data from the voyages that have been taken since the system installation are still being analyzed, but so far everything is looking promising, Orca AI’s co-founder said.

The Orca AI system can be used on any vessel – size is not an issue, as the sensor payload is not very large or intrusive. However, the company is focusing on larger vessels first, as the challenges of collision avoidance and costs of collisions are most pronounced for this class of ships.

“Orca AI’s navigation system is fit for all types of vessels, using information from sensors already on board and supplementing them with cameras of their own in a relatively small payload. We are looking forward to working with different classes of ships, helping them safely navigate crowded waterways and avoid collisions in hard-to-see situations where their difficulty in rapidly adjusting course makes early detection of other ships a priority,” Gross told WMN.

When asked what are the prerequisites for the installation of the Orca AI solution, Gross pointed out that there are no impediments to installing the system on any ship type. The installation is said to be straightforward and the system is easy to integrate on the bridge, so the age of the ship has no impact on the process.

AI and the maritime industry

Several autonomous vessels projects are currently being developed around the world. As informed, Orca AI is in discussions with the large technology providers that are building the eco-system for the future of autonomous vessels. Gross noted that these companies understand that they cannot build everything by themselves, so they are seeking partners to collaborate with.

“An autonomous vessels are like a puzzle, there are many crucial pieces that all need to fit together, and we are trying to build the best technology in the world for one of the most important pieces of the puzzle,” according to Gross.

Artificial Intelligence, which has been the buzzword over the recent time, is becoming increasingly important for the maritime industry as well.

“AI is a tool for solving problems that have been hard to solve until now. For the maritime industry, it is enabling us to tackle issues such as detection of ships and other items on the water, and alerting and assisting the captain and the crew with the navigation of the ship,” Gross said, adding that AI is also helping solve many more problems in the industry such as logistics, predictive maintenance, internal operations, etc.

“I think that for certain use cases AI is already able to provide real value, and as the maritime industry continues to adopt AI solutions and develop them, we will see increased efficiency and safety, as well as seeing a reduction of costs across the board,” Gross concluded.

At the end of January 2019, Orca AI closed a funding round, raising USD 2.6 million. With the help of the new funds, the company plans to grow its engineering ranks and establish an office in Europe this year.

Orca AI’s key steps for moving forward will be to continue installation of the company’s system onboard more ships, which has so far proved to be a major success. Additional partnerships with other shipping companies are currently in the works and Orca AI is ramping up production to meet the growing demand.

Source: World Maritime News

Automation forces Spain to introduce structural changes in logistics

The transport and logistics sectors are currently in the process of automation. In the coming decades it will undergo deeper transformations, which will test the reaction capacities of countries such as Spain. “We must be creative in changing our way of thinking. There is a lot of work to be done in the short term, in short electoral cycles, by survey, and there are structural changes that must be applied in the medium and long term, “says Inprous CEO and president of Pimec Logística, Ignasi Sayol.

For his part Miquel Serracanta, the founder of the consulting firm Solutions & Decisions, put the emphasis on how the increase in competition “has caused a very important fall in prices both in the trunk and in capillary transport”, so that the carriers that have increased in size have started to search for synergies and efficiencies in their supply chains in parallel. For this reason, he considers that it is necessary to prepare for changes such as the electric and autonomous vehicles, since “they will substantially modify our environment in the next ten years”.

Globally, transformations will involve changes in jobs and new trends will be developed that will improve the efficiency of deliveries. Although technological advances will be inevitable, they will occur gradually and will vary according to the region. These are some of the results published in the new report prepared by the International Transport Workers’ Federation (ITF) and the World Maritime University (WMU).

Evolution vs Revolution

Although the report foresees that the automation of global transport is more “evolutionary” than “revolutionary”, Sayol affirms that “the irruption of technology in logistics will radically change the way we do things”. Gradual changes are expected in transport patterns that will affect the different regions of the world. According to Serracanta, autonomous vehicles “will not arrive for another five or ten years and will do so progressively, coexisting therefore, with difficulties, with vehicles driven by humans.”

The partner founder of Solutions & Decisions foresees that automation will make roads safer and that fewer accidents and traffic jams will occur, “with which the reliability of compliance with deliveries will increase”.

Sayol points out that logistics 4.0 will be an opportunity for developing countries, “because they can implement it without the mortgages that exist in developed countries.”

“Automation will probably reduce the differences between developed and developing countries in the medium and long term, once the latter can be added to the technology train,” says Serracanta. However, it considers that in the short term it is possible to increase them, especially in terms of road and rail transport: “Those who are in the process of development may not be able to start this road yet due to previous pending issues, as indispensable basic infrastructures”.
Worldwide, it is expected that transportation routes will also change if situations such as a hypothetical stagnation of China or the growth of Mexico are consolidated. If confirmed these trends, directly affect the GDP of the countries. However, this forecast does not apply to long-distance maritime transport, which will continue to be the main means in terms of scale and volume of goods transported. In contrast, a reduction in road transport is expected both in the EU and in the countries of Southeast Asia, as well as growth in the maritime sector, because “it is still in an early stage of transformation,” according to the study.
The Impact of Automation on employment
Automation will impact the transport sector through the destruction, displacement and creation of jobs. Workers will be affected differently according to their level of skill and preparation, with the least educated being the most affected. This will require the retraining of professionals such as cargo agents and crane operators so that they can work complementarily with this technology, notes the report of the International Transport Workers Federation (ITF) and the World Maritime University (WMU). However, despite the high levels of automation, human resources will still be necessary, especially in cases where people provide additional value.
“The challenge will be twofold, for the companies that have them on staff and for the worker himself, who must improve his own employability with additional training if he does not want to lose possibilities in his current and future position,” says Serracanta. “The repetitive tasks and added low value are the first at risk of being replaced by robots, and workers who today are the first to be recycled.” In fact, today automated metro lines are already operating, such as the one that connects the city of Barcelona with its airport, or the one that connects the two passenger terminals of the Frankfurt airport in Germany.
Logistics 4.0
In addition to the automation of vehicles, infrastructures and processes, the new logistics 4.0 will allow technologies such as Big Data or artificial intelligence to be progressively applied to know what the client wants, anticipate demand and position stocks at the suitable point. “It sounds like science fiction, but it’s already a reality,” says Sayol.
The CEO of Inprous also includes the internet of things (IoT) and blockchain in this group, which “will enable the creation of dis-intermediated and efficient marketplaces that allow for optimisation and secures the available transport resources”. Finally, “more complex technologies to apply in reality” will exist, including platooning. “Here the time horizon of implementation is more difficult to get right, as it is subject to the legislation of each country and investments in infrastructure that inevitably must be made,” he explains.
According to Serracanta, this automation and logistics 4.0 will also allow for the “reduction of consumption and fuelling of large trucks, because they are more efficient than humans, with which there will be less CO2 emissions and the environment will appreciate it”. Thus, an evolution is foreseen in the logistics transport sector that will bring economic benefits and that will entail new regulations, a greater technological preparation and the development of new skills and dynamics in the labor market.
Source: El Mercantil

Artificial intelligence: Ports are beginning to take up positions

Artificial intelligence (AI) is an affordable technology, although it is only slowly being introduced into the business sector. Thus far, it has primarily been used to improve sales prediction techniques, but its potential applications are infinite and include lowering maintenance costs, improving product quality, planning manufacturing and increasing service level. In the sphere of transport, AI opens up a host of possibilities. Will the ports take advantage of them?

Today, the ports of Hamburg, Rotterdam and Singapore have already started to develop AI tools to improve predictions of maritime and land transport operations. Specifically, Hamburg has created a decision-making support system based on a predictive model of the behaviour of land transport. The model takes historical data, and using deep learning techniques and neural networks, it offers detailed predictions of the times when lorries should reach terminals. Based on this, the system notifies the lorry drivers of the terminal entrance times, and it gives the terminals a dynamic forecast of the workload they will have according to the changes in the surrounding conditions (road and access route saturation, real ship arrival time, degree of terminal saturation, etc.).

HOW DOES DEEP LEARNING WORK?

Deep learning and neural networks are two of the machine-learning methods which have come to the fore the most in recent years. They are inspired by the way neural networks work in the brain. They transform the entry values, layer by layer, until the value of the variables that they are trying to predict is found. Even though the results of neural networks are quite satisfactory, they need vast amounts of data to learn, and learning times are long (days or even weeks). Natural language processing, image pattern recognition and voice processing are the main success stories of deep learning. Thus, the evolution of data collection and management has to include the following levels: recording, analysing, simulating, predicting and finally recommending. Based on that, new-generation ports are expected to apply predictive and prescriptive analysis techniques as tools to support decision-making when planning the transport of the actors in the port-logistics chain. And this does not only include lorries, since the same transport logistics that it applied on motorways can also be applied to any means of transport (railway, maritime or river).

New-generation ports are expected to apply predictive and prescriptive analysis techniques as tools to support decision-making when planning the transport of the actors in the port-logistics chain.
The digital transformation in the port and the logistics chain entails huge amounts of data, many of them in real time. The competitiveness of future ports will largely depend on their ability to make use of this information. With AI tools that enable them to take advantage of the potentiality of this vast trove of data, the decisions taken by the managers will be higher quality, shared and generated more quickly, so they will likely optimise the time, cost and reliability of the operations in port-logistics environments. In a complementary fashion, all of this will end up leading to more flexible, real-time operations management. AI has reached the world of transport, and it is here to stay. The ports which realised its benefits and potentiality to change the sector first will unquestionably see operational efficiency gains compared to their competitors. Ports that already have advanced systems that allow them to gather a significant amount of data (Port Community Systems, Port Management Systems and Terminal Operating Systems, among other systems) will be the best poised to successfully incorporate the tools offered by artificial intelligence.

Ports that already have advanced systems that allow them to gather a significant amount of data will be the best poised to successfully incorporate the tools offered by artificial intelligence

THE ORIGINS OF ARTIFICIAL INTELLIGENCE

Even though it seems like a recent concept, the origins of artificial intelligence date back to the Greeks. Aristotle (384-322 BC) was the first to determine a set of rules that partly describes the way the mind works to reach rational conclusions, and Ctesibius of Alexandria (285-222 BC) built the first self-controlled machine, a water-flow regulator (rational, but without the ability to reason). John McCarthy, Marvin Minsky and Claude Shannon coined the term artificial intelligence at the Dartmouth Workshop (USA) in 1956 to refer to the “science and inventiveness of making intelligent machines, especially intelligent calculation programmes”. Where these three scientists missed the mark was in their prediction of when the first smart machines would arrive. They trusted that by the 1970s we would be surrounded by artificial intelligence. However, the majority of tech companies did not decide to make significant investments in this field until the 1990s and 2000s, in a bid to improve the processing and analytical capacity of the vast amounts of data which were being generated in the new digital world. In fact, AI was definitively enshrined in 1997, when IBM demonstrated that an IT system was capable of beating a human at chess. And it wasn’t just any human; it was the world champion, Garry Kasparov. The supercomputer was called Deep Blue, and it marked the turning point when industrial technology and society at large became aware of the real importance and possibilities of artificial intelligence.

Source: PierNext