Fishermen Turn to Apps and AI to Tackle Climate Change

From weather predicting apps to using artificial intelligence to monitor the fish they catch, small-scale fishermen and coastal communities are increasingly turning to digital tools to help them be more sustainable and tackle climate change.

Overfishing and illegal fishing by commercial vessels inflict significant damage on fisheries and the environment, and take food and jobs from millions of people in coastal communities who rely on fishing, environmental groups say.

In addition, climate change affects on small-scale fishermen—who account for about 90% of the world’s capture fishermen and fish workers—include fish moving to new areas in search of cooler waters or if their habitat is destroyed, rising sea levels, and an increase in the number of storms.

Launched in January by nonprofit Environmental Defense Fund (EDF), the Small-Scale Fisheries Resource and Collaboration Hub (SSF Hub) is a multilingual website that aims to bring together fishermen, their communities and advocacy groups to connect, share ideas and find solutions to the problems they face.

“Small-scale fishers are already facing many challenges—from multiple marine uses, declining fish stocks, threats from over-fishing—and climate change is just going to exacerbate those challenges,” said Alexis Rife, director of small-scale fisheries initiatives at EDF.

“That means that their livelihoods are at risk. It means that their food security is at risk … it’s a pretty dire situation,” she told the Thomson Reuters Foundation.

The website has a resource library where fishermen can search for topics of interest, free online courses, a community forum, discussion groups, an events page and a blog section.

Although it requires a smart phone or computer and internet connection to access—which is often patchy in coastal areas—Rife said it had low data requirements and they are looking at ways to enable users to view its information offline.

The website’s resources can be easily shared via WhatsApp, Facebook or Twitter—platforms already widely used by many small-scale fishers to help get the best prices.

EDF also has a pilot project in Indonesia’s Lampung province on Sumatra island that uses an app to record and monitor catch in blue swimming crab fisheries to enable them to be more sustainable.

A separate pilot in Indonesia uses cameras with artificial intelligence (AI) and algorithms to monitor how many vessels are going out to sea and estimate their catch.

“Fishing is the backbone of coastal and inland fisheries communities around the globe, providing food and nutrition, supporting fishing-related jobs … (and) helping alleviate poverty,” said Simon Cripps, executive director for marine conservation at green group the Wildlife Conservation Society.

Find a balance
Since 2007, Taiwan has mandated that all small-scale fishermen use global positioning system (GPS) devices—that give a vessel’s location every three minutes—with the data collected and analyzed along with reports on fish catches, gear used, and auctions.

The data and monitoring gives insight into assessing fishery conditions, fisheries livelihoods and food security, and helps shape government policy.

The system was also used in 2016 to estimate loss of earnings and allocate reparations to fishermen after an oil spill.

“This year, the device has been rather helpful in assessing fishery conditions and for offshore wind power farms—trying to find a balance between the environmental protection, fishing ground, and power industries,” said William Hsu, associate professor at the National Taiwan Ocean University, which helped with the project.

To alleviate privacy concerns, the government gave assurances that the data would be kept private unless ordered by a court and instigated fuel subsidies as an incentive for users.

In South Africa, the Abalobi app for small fisheries was launched about five years ago and enables users to log catches, record fish sales, capture daily expenses, find buyers and see the latest fishing regulations and notices.

Simon Funge-Smith, senior fishery officer at the United Nations’ Food and Agriculture Organization (FAO) in the Asia-Pacific, said while many technologies can be useful for advocacy groups, fishers’ groups and researchers, their benefits to small-scale fishers are limited.

Language, limited coverage of phone networks, and data requirements, can hold back many technologies, he said.

Apps that track locations and fish catches using less time-consuming and simple entries, or help users comply with rules and laws, are more likely to succeed in empowering small-scale fishermen, he said.

Mobile phones and online banking apps have “transformed” fishing and “lubricated the entire trading arrangement of what is a very perishable product”, Funge-Smith said.

The threat of data collected by digital tools being misused—like for taxation—is not huge, he said, adding that this would discourage its use or cause its misuse.

Ohi Masuda has been a geoduck and scallops fisherman for more than a decade near Baja California, Mexico, maintaining a family tradition that began when his ancestors came to Mexico from Japan in the 1950s.

Masuda has to cope with rising sea temperatures impacting the types of fish he can catch, and the need of cool water for the processing of fish before being shipped to Asia.

“It could help us to innovate,” he said about the SSF Hub, while conceding that limited internet connection could hinder access for some fishermen.

“In Mexico, we often believe that we need to concentrate our efforts only on catching enough fish to sustain a fishery without investing in post-harvest processes, transportation, added value, management, or distribution.”

(Reporting by Michael Taylor; Editing by Belinda Goldsmith; Credit: Thomson Reuters Foundation)


Siemens Gamesa books Reygar vessel monitoring boost

Reygar has been commissioned by Siemens Gamesa to develop a motion comfort monitoring tool capability within its BareFleet remote monitoring and reporting platform for vessels supporting multi-day work at the manufacturer’s projects.

The new system will track and analyse motion, fuel consumption and crew sickness in different cabin locations, with a specific focus on boosting safety and fitness to work aboard vessels.

Reygar said the system that Siemens Gamesa has commissioned automatically monitors the health and performance of critical equipment across each vessel, inclusive of engine health, CO2 emissions, fuel consumption, motion, and impact onto the turbine.

The tool also allows the crew to manually input supplementary data and observations into a customer-specific digital reporting platform, with the resulting DPR form customised to bring Siemens Gamesa’s own performance indicators and priority data fields – such as crew comfort – to the fore.

Reygar managing director Chris Huxley-Reynard said: “As wind projects move further offshore into areas of higher wind resource, it is paramount that charterers and vessel operators are equipped with the true understanding of vessel motions and personnel comfort they need to keep these projects – and the people constructing and maintaining them – performing at their best.

“Motion data measured across different cabin locations and different vessels, sourced via BareFleet while in transit and while idling, will advise Siemens Gamesa’s chartered vessel operators on how to guarantee the crew and technicians are housed and transported in such a way that they can continue do their jobs effectively across multi-day projects.”

Siemens Gamesa head of offshore service logistics Rene Wigmans said: “With the global energy transition well underway, we are increasingly focused on how digitalisation can power the efficient and safe roll-out of our technology across projects in exciting, rapidly growing markets such as the US and Taiwan.

“Our work with Reygar to further integrate BareFleet’s detailed motion reporting into our offshore activity will support our team in maximising operational efficiency and reducing vessel CO2 emissions whilst securing the health and comfort of our crew as they work on these flagship – yet often remote – sites.”

Source:, 2020/12/14

AI is Helping Scientists Understand an Ocean’s Worth of Data

If you had about 180,000 hours of underwater recordings from the Pacific Ocean, and you needed to know when and where, in all those different hours, humpback whales were singing, would you Google it?

That is what Ann Allen, a research ecologist at the National Oceanic and Atmospheric Administration, did. Sort of.

In January 2018, she approached Google and asked if they might be able to help her find the signal of humpback whale songs amid all the other ocean noise, like dolphin calls or ship engines. Using 10 hours of annotated data, in which the whale songs and other noises were identified, Google engineers trained a neural network to detect the songs, based on a model for recognizing sounds in YouTube videos, said Julie Cattiau, a product manager at Google.

About nine months later, Dr. Allen had a model for identifying humpback whale songs, which she is using in her research on the occurrence of the species in islands in the Pacific and how it may have changed over the last decade. Google used similar algorithms to help Canada’s Department of Fisheries and Oceans monitor in real time the population of the endangered Southern Resident Orca, which is down to around 70 animals.

Machine learning and artificial intelligence applications are proving to be especially useful in the ocean, where there is both so much data — big surfaces, deep depths — and not enough data — it is too expensive and not necessarily useful to collect samples of any kind from all over.

Climate change makes machine learning that much more valuable, too: So much of the data available to scientists is not necessarily accurate anymore, as animals move their habitats, temperatures rise and currents shift. As species move, managing populations becomes even more critical.

To protect the whales, scientists need to know where they are, which is what the Charles Stark Draper Laboratory and the New England Aquarium are doing in what they call “counting whales from space.” Taking data from satellites, sonar, radar, human sightings, ocean currents and more, they are training a machine-learning algorithm to create a probability model of where the whales might be. With such information, the federal, state and local authorities could make decisions about shipping lanes and speeds and fishing more quickly, helping them to better protect the whales, according to Sheila Hemami, director of global challenges at Draper.

Many fish populations are moving, too, or are overfished or nearing it, and much of that fishing is done illegally. In an effort to clamp down on illegal activity and keep populations at healthy levels in the ocean, Google also helped start Global Fishing Watch, an organization that monitors fishing around the world by collecting and making vessels’ positions and activities public.

“The oceans are a pretty exciting place to work in big data because there’s so much opportunity for improving data, which, in fisheries has historically been very poor, especially when you compare it with other extractive industries,” said David Kroodsma, Global Fishing Watch’s director of research and innovation.

“Twenty percent of fishing is illegal, unreported or unregulated,” he said. “What if we didn’t know where 20 percent of the forests were, or carbon emissions?”

Other applications are used in ocean chemistry and pollution, for tasks like monitoring ocean plastic. Using sensors similar to those that monitor air quality in the International Space Station, Draper is collecting data on the properties of microplastics found in the ocean at the request of the Environmental Protection Agency. From that information, they produce “a fingerprint of specific chemicals,” said Dr. Hemami, and use that fingerprint to train the algorithm to identify kinds of plastic.

They are still in the testing phase, but have deployed their first-generation sensor near the Northern Pacific gyre, home to the Great Pacific Garbage Patch, which helped provide information about how the system might work.

Machine learning has not yet been widely used in assessing other issues in ocean chemistry, like ocean acidification, deoxygenation or nitrate concentrations, but Dr. Hemami said there was significant promise in that area.

In at least one case, animal observation applications and the more chemically focused ones overlap. They come together in shared pursuit of the giant larvacean.

Kakani Katija, a principal engineer at the Monterey Bay Research Aquarium Institute, has been using machine learning to track the lives of these zooplankton, which build themselves elaborate houses out of mucus, and model their behavior. In their snot-bubble homes (which can exceed three feet), the tiny animals (about half the length of a new pencil) filter water, in the process capturing particles and detritus sinking from the surface of the ocean to eat.

Once the structure is clogged with this ocean dust, much of which is made up of photosynthesizing organisms that have pulled down atmospheric carbon dioxide in the process, the animals abandon their homes, which sink to the ocean floor and feed bottom dwellers. But they have another crucial function: In trapping all of that debris, the mucus houses are sequestering carbon dioxide, sending it to the bottom of the ocean.

As we burn fossil fuels, we release carbon dioxide, much of which is absorbed by the oceans. The oceans have, as a result, prevented our planet from warming by as much as 36 degrees Celsius (instead of about one degree), but all of that carbon dioxide makes the oceans more acidic. Knowing how much carbon dioxide the ocean is storing is crucial to modeling future climate changes, and given the prevalence of these creatures around the world and how much water they can filter, it is likely a significant amount.

“With the oceans or the environment, it’s really easy for us to get stuck in this doom-and-gloom narrative,” Dr. Katija said. “What I love about technology or the progress we’re seeing in A.I., I think it’s a hopeful time because if we get this right, I think it will have profound effects on how we observe our environment and create a sustainable future.”

Source: New York Times, Apr 8, 2020


The Maritime and Coastguard Agency (MCA) has partnered with artificial intelligence technology company, Faculty, on a major programme to build the next generation of UK search and rescue.

Faculty is using advanced analytics and machine learning technology to analyse historical data on 9,000 search and rescue mission requests covering 43 months. MCA is working with Faculty to generate simulated missions data to test the robustness of its findings.

“Every day the UK’s search and rescue fleet is out saving lives and we’re immensely proud to be working with it,” said Tom Nixon, director of Faculty’s government practice. “Taking this step puts the MCA in the vanguard of data-driven public services and shows the important role data science can play in supporting the procurement process,” he added.

The work will help inform planning for the successor to the UK’s search and rescue helicopter capability, Search and Rescue 2nd generation (UKSAR2G). Faculty is working with the MCA to design simulation tools that will allow aviation partners bidding for UKSAR2G to virtually test performance against a variety of future scenarios.

The UK’s search and rescue helicopter fleet, with its distinctive red and white livery, comprises 21 aircraft operating from ten locations across the UK.

By Rebecca Strong

Source: Maritime Journal, Oct 23, 2020

Microsoft and SES invest in maritime cloud solutions

Data Analytics & Digitalisation to Drive Global Shipping Industry

In the age of digitalisation ‘Data’ is a key asset. Especially in the post-COVID scenario, the industrial sectors are going to rely on data to drive businesses. The maritime sector is no exception as it generates a vast pool of data collected from various sources, onboard vessels and while the ships are berthed.

Data analysis allows the growth of vessel support network and improves safety. In addition, the study of data has helped in making ship management more economical, in terms of cost and time both. Onboard, the seafarers use data to chart short-term course of action with ‘predictions’. Right from collection, analysis to interpretation of data, the shipping industry is tapping at every possible source and technology to better utilize the data.

For instance, predictive analysis has become the new hotshot in the industry. Predictive analysis can be defined as using data, statistical algorithms and machine learning to determine the likelihood of future events and outcomes.

Through predictive analysis, it has become easier for the decision-makers in the industry to enhance operations both off-shore and on-shore. Right from maintenance, to predicting the weather conditions at the sea, to achieve the post-optimization, analysis of historical and real-time data is playing a cardinal role in increasing operational efficiency.

While discussing the importance of data analytics, it is necessary to take a look at the evolution of data collection and analysis. The history of data analysis allows us to understand the significance of data from the very beginning, making it quite clear that data has always been a key driver for lifting operational standards of the sector.

According to experts, maritime data analytics has already witnessed 3 ages and is about to enter the 4th age. The below-mentioned timeline shows the evolution of data analytics and the significance of data collection and analysis in each age:

The first era began in 1734 when Lloyd started listing vessels and their cargo arriving at London. The first age is at times referred to as the age of chit-chat.

The second era, which can be said to have started around 1988 is also known as investigative age. It was the time that marked the arrival of IMO number of the ships along with the internet. With internet paving its way, a number of online shipping databases were produced with analytical features. Lastly, the era gave SIN to the industry which remained a de facto shipping database for a number of years.

We are presently in the third age of maritime analytics. The age has witnessed a remarkable growth and expansion of data as an asset. Big Data algorithms are playing a crucial role in the growth of the sector by allowing the shipping companies to use the database to gain more commercial advantage.

The fourth era, as experts believe, could be dedicated to crowd-sourcing of maritime data. The sector has already realized the value of data and in the future, it is expected to focus on using the information directly from the crew of the ships. This is one significant part that is yet to be exploited to fetch intimate specification of the ships. If the sector is able to achieve the target, the maritime database will be more accurate and safe.

An average ship generates 2 GB of data on a daily basis when at sea. This is huge amount of data which can be effectively used in operation, maintenance or even accomplishing the daily chores (trivial) onboard. It all depends on effective use of data analytics or IoT, for making the most out of the data generated by the ship.

Efforts are on to implement global maritime data analytics in much better ways so as to establish consistent growth. We are now at a critical turning point where good investments are flowing in for ‘technology in maritime’, especially the data analytics sector.

The Way Ahead:

A lot needs to be done to adapt in the changing landscape of data, software and the consciousness of the stakeholders (of shipping & maritime) has to grow. Much like the Internet did 20+ years ago, data analysis and the IoT is going to change the world around us. No single company can do it all alone anymore. Right investment and a wise selection of technology is the key to digital transformation. A collaborative innovation will keep the industry evolving today and prepare it for what unfolds in the future.

The COVID-19 crisis is evolving rapidly, creating considerable challenges for the logistics, supply chain, shipping and maritime sectors. Amid such a scenario, Data analytics and technology adoption is expected to gain traction during the post-COVID phase, which is expected to stabilise the maritime industry and drive it towards growth.

Source: Sea News


Can aquaculture go all-in on AI?

High-tech solutions like artificial intelligence are making inroads in aquaculture. Can AI drive further growth?

Aquaculture has long depended on the intuition and experience of farmers in areas such as feeding or disease prediction. Today some companies are harnessing the power of artificial intelligence (AI) to improve operations.

In Japan, where the population is aging and the workforce is shrinking, efficient farming operations are crucial. Umitron, an aquaculture technology provider in Japan and Singapore, offers data platforms using IoT, satellite remote sensing and AI. One of its recent solutions is UMITRON CELL (CELL), a smart fish feeder that holds 400 kg of feed and includes a solar-power management system, onboard computer, weight sensors, dispensing motor and a camera for observing fish 24 hours a day. The feeder is remotely controlled and fish videos are monitored with a smartphone or desktop computer.

“CELL’s development came from discussions with farmers who struggled to monitor all their cages and feed the correct amount each day,” said Andy Davison, product manager at Umitron. “They didn’t typically take weekends or holidays since they needed to visit their fish cages every day to feed the fish and monitor their condition. CELL allows them to accurately manage their feed and stay onshore occasionally while still monitoring their fish.”

CELL is installed on cages and allows farmers to check a live stream or saved video data. The farmer can adjust the feeder’s timing and amount settings to fine-tune feeding, and check historical feeding and fish data to see the amount of feed used over the past day, week or month. The system is remotely powered by a solar panel connected to a battery. CELL is now being used in tandem with Umitron’s latest AI-powered algorithm Fish Appetite Index (FAI), a real-time ocean-based fish appetite detection system in which machine-learning algorithms analyze video data collected directly from farm sites to calculate fish appetite. Farmers can check FAI metrics to determine when their fish are hungry or full and adjust feeding accordingly.

Farmers can check FAI metrics remotely to adjust feeding schedules according to fish behavior.

“They can obtain more information on their fish’s behavior and move toward data-driven decision-making to further optimize feeding schedules,” said Davison. “FAI reduces wasted feed, improves profitability and environmental sustainability, and offers a better work life by eliminating the need to be out on the water in dangerous conditions. It also reduces the need for every employee to be a feeding expert and frees workers to focus on other tasks that improve fish welfare.”

Japan has a robust environmental regulatory system for aquaculture and requires permits that specify the size and location of offshore farms. Davison says that with more efficient feeding and data collection, it may also become possible to specify precisely how many farms should be located in a given area, potentially allowing aquaculture to use available space more efficiently.

Meanwhile, other firms are also tapping into the potential of AI. Aquaconnect, a startup in India, is helping shrimp farmers predict disease and enhance water quality with its mobile application FarmMOJO. The tool uses machine-learning technology to provide insights and suggest appropriate steps.

“Smart technology is key to better productivity and disease management. It accelerates rapid detection, real-time reporting and data-driven decision-making,” said Rajamanohar Somasundaram, CEO and co-founder.

An example of Fish Appetite Index (FAI) data and the traffic light warning system of green, yellow and red to indicate good, OK and bad appetite levels, respectively.

AI in aquaculture appears promising, but just how far could it revolutionize the industry? Its importance will depend a lot on the species and farming methods involved. Commodity seafood markets like shrimp and salmon, where global competition sets the price, will require data and AI to stay competitive. Countries with strict environmental guidelines and environmentally conscious consumers could use AI to improve product traceability and marketability. However, for lower-value species that are typically consumed locally, investing in AI may not make financial sense.

Davison believes that amidst growing awareness and technological improvements, AI is likely to be adopted in full.

“As soon as its advantages are better recognized, we could see a mass adoption and that may revolutionize aquaculture,” he said. “But adopting new ideas and technologies takes time. This can be frustrating, but what we may consider slow adoption could just be the regular speed of adoption.”

“AI, real-time sensors and IoT have many advantages. They can identify water quality changes at the initial stage and detect changes in the consumption and growth pattern of animals or help farmers take preventive measures before a disease outbreak,” said Somasundaram. “Aquaculture stakeholders should focus on the innovation of affordable IoT devices and farming equipment to facilitate the continuous monitoring of water quality, animal performance and growth.”

The newest version of CELL.

But challenges remain. With data security awareness growing, some farmers want to know how their data are being used and by whom. Explaining the specific steps taken to ensure that data are transmitted and stored securely is in itself a challenge, says Davison, with specifics on encryption, keys and HTTPS protocols lost on the average technology user. This makes it all the more crucial for firms to be good stewards of their customers’ data and maintain trust. Somasundaram agrees that technology often poses a steep learning curve among farmers.

“Fish and shrimp farmers have always worked through word-of-mouth advice from their peers and will need to be guided when adopting technology. Incentives, training and adequate exposure may help,” he said. “Data ownership and security haven’t yet gained much attention among farmers, so the government and stakeholders must engage in conversation and create standards for both. This could be a great challenge in future for multinational firms that want to offer their solutions in multiple geographies, where each country may have its own standards.”

A final dilemma, according to Davison, is what to do with all of the data that you now have.

“It’s easy to be overwhelmed with new sources of data but not have established methods on how to process and use all that information to make better decisions,” he said. “All that data is useless unless companies have a way to use it.”

With time, hard work and clever people, many traditional industries including aquaculture could become fully automated. Making good use of the power of science and technology to improve efficiency and increase yields is likely to produce significant results.

“To increase AI’s adoption, we need to appeal to farmers on a rational and emotional level,” said Davison. “When a farmer realizes they no longer need to work seven days a week thanks to AI, that greatly impacts their lives. On the rational level, when we can clearly demonstrate increased profitability with AI data-driven decision making and automation, we’ll see a big uptick in use.”

Source: Global Aquaculture Alliance

AI Provides Solutions for the Japanese Fishing Industry

In the 1990s farmed fish (aquaculture) accounted for about one-quarter of global seafood production according to the UN Food and Agricultural Organization. Now, with demand rising and the ocean’s resources being steadily depleted, aquaculture has overtaken wild fishery, globally producing more than 100 million metric tonnes of seafood each year.

Artificial intelligence is increasingly used in aquaculture management to analyze water conditions, environmental changes and fish status. And nowhere are these emerging fishing industry technologies more important than in Japan.

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According to a report by private research group Yano Economic Research Institute, Japan’s aquaculture market will reach JP¥20.3 billion in 2021, an increase of 53 percent from 2016. AI-powered smart fisheries will account for JP¥1.3 billion, a figure that is rising quickly.

The aging of Japan’s primary fishing industry and the lack of successors reflect larger social issues related to the country’s aging population and declining birthrate. Wild fisheries are also increasingly constrained by resource conservation efforts, which has dealt a double blow to the Japanese fishing industry.

This article looks at three Japanese cases where AI is being applied either in large-scale aquaculture or to improve yields in traditional capture fishing.

Live weight management of fish by underwater camera

Aquaculture operations need to provide different amounts of feed depending on the weight of fish in their farms. Currently, if 50,000 fry are being raised in a breeding area, at least 200 fry are randomly sampled each time operators want to determine average weight. However, 200 of the 50,000 fry accounts for only 0.4 percent of the total, and so weight estimates may be inaccurate due small sample size.

Nippon Steel, in cooperation with NEC, is testing and deploying an automated underwater shooting system that captures images with a stereo camera. These are then processed frame by frame by an AI system that can determine fry size and weight by analyzing feature points, such as the tip of the fish’s nose and the size of its spine. The system can save time and reduce labour costs while improving accuracy.

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Optimizing income and expenditures with AI

Environmental factors such as water temperature, salt concentration, meteorological conditions, tides, wind direction, wind speed, carbon dioxide level and age all affect the appetite of fish. For efficient fish stock management AI can analyze these factors to determine real-time state of the fry provide the correct amount of feed. An AI system provided by Nippon Steel can reduce feed amount by 60–70 percent to significantly lower production costs.

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capture Fishing analysis AI

Sasebo Kokai Sokki, Sasebo City, and Nagasaki Prefecture are cooperating in the maintenance of navigation and marine meteorological observation equipment for capture fishing. The aim is use fishery AI to offset the declining number of fishery workers. The system considers market demand and advises fishermen how to adjust their catch accordingly to prevent fish prices falling due to overfishing. This can reduce both the working hours of fishermen and the fuel costs of fishing boats to stabilize the income of fishermen while reducing waste to better protect natural resources.

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In this case the AI is largely trained by the fishermen themselves. The system logs the daily catch, seawater temperature, and fishing area. Past marine weather data from other data sources is also added to enable the AI to understand the relationship between fishing yields and weather conditions. Sasebo’s fishery app considers maps, operational diaries, weather data, tides, temperature, captured fish, etc. to guide fishermen on how to increase yields for each fishing session.

AI’s Future in the Japanese fishing industry

Japan’s fishing industry can be divided into two major categories: deep-sea farming and capture fishing. The former can use AI to analyze the growth state and feed requirements of fish; while AI can help the latter with analysis of data such as weather, catch, and ocean currents. Whether in real-time analysis or in complex conditional judgment, AI has far more power and potential than humans for these tasks.

Humans working in the traditional fishing industry need to learn their skills from mentors and through direct experience, and identifying and correcting mistakes is challenging because the natural forces the industry deals with are constantly changing. The aging of Japanese fishery workers has also created a labour shortage that is negatively affecting productivity. AI can offer solutions to these problems, particularly by engaging tech-savvy young Japanese who might not have otherwise considered entering the fishing industry.

Source: Medium

Opening Ceremony of Mediterranean and Asia Marine Alliance

Ocean is the asset of all human kinds in the world. Ocean resources bring enormous functions and benefits to human beings, and are the important assets for the living and development of generations of Taiwanese people.

Taiwan is surrounded by ocean. Being an Ocean Nation, ocean affairs has significant strategic implications. The recent confrontation of USA and China with intensive military exercises in the South China Sea has accelerated geopolitical wrestling to an unprecedented level, which further demonstrates the importance of ocean governance and national maritime rights. In April 2018, Taiwan government established“Ocean Affairs Council”, a ministry level agency; in November 2019, the “Ocean Basic Act” is passed and promulgated; and in June of this year (2020), the new edition of “National Ocean Policy White Paper” is issued and released. These consecutive actions strongly demonstrate the government’s emphasis on ocean policy and affairs, its proactive measures to encourage national people to focus on ocean related issues, and its determination to achieve the sustainable development of ocean.

Mediterranean is also an important geopolitical center in the world, and Israel is an important country in the Mediterranean area. Due to the complementary development of technology and economy, there are increasing interactions among Taiwan, Israel and Mediterranean area in recent years. Now it is the best time to connect resources across the regions through the dialogue of ocean.

Mediterranean and Asia Marine Alliance (abbreviated MAMA) is jointly established by Lian Tat Company (LTC) and Tunghai Industry Smart-Transformation Center (TISC), with deep cooperation from Israel strategic partners. This is the first platform initiated and established by private enterprise and organization in Taiwan to facilitate the cooperation and interaction of industry, government, and academic sectors in Taiwan and abroad. The Alliance is founded responding to government’s call and expectation for private sector to assist in promotion of marine related research and affairs, and to align with global ocean trends.

MAMA is composed of six areas of Ocean Policy, Smart Ocean, Ocean Biology, Ocean Resources, Ocean Industry and Ocean Culture. By chaining resources of each area, the Alliance is aimed to promoting ocean related research, providing policy advice, creating cooperation of industry and academia, fostering international exchange and cooperation, and upgrading Taiwan’s world visibility in participation of ocean affairs.

Time: September 23, 2020 (Wed) 2:00 pm
Place: B1 East Gate, Shangri-La’s Far Eastern Plaza Hotel
Address: 201 Tun Hwa S. Road, Sec. 2, Taipei

New marine heatwave early warning system for the Australian aquaculture industry

Australia’s $3 billion fisheries and aquaculture industries will receive up to six months’ warning of damaging marine heatwaves under a national forecasting system developed by the CSIRO and Bureau of Meteorology.

Written by: Mike Foley /

The sea surface temperature around Australia has warmed by about 1 degree since 1910, according to the bureau, with eight of the 10 warmest years on record occurring since 2010.

The warming trend has increased the rate of marine heatwaves – when the sea surface temperature sits in the upper band of historical averages for at least five days. Marine heatwaves can stress fish, damaging the output of fish farms by reducing yield, quality and spreading disease. They are also a chief cause of coral bleaching, which is a major threat to coral ecosystems such as the Great Barrier Reef.

“By giving advanced warning, marine industries and managers of fisheries and aquaculture would be able to take action to minimise impacts of these damaging heatwaves on their stocks and marine resources,” said federal Environment Minister Sussan Ley, whose department funded the $300,000 project.

With advance warning, aquaculture managers can harvest ahead of a temperature spike, relocate their operations or deploy short-term solutions such as water-cooling systems or shading for fish pens.

The modelling for the system, which is powered by the Commonwealth’s $77 million Cray XC40 super-computer, can also show which locations are most at risk of heatwaves and help pinpoint the most advantageous farm sites.

Australia’s marine industries, including aquaculture, tourism and marine engineering and boat building, contribute more than $50 billion a year to the economy and the government is forecasting this to grow to $100 billion by 2025.

While heatwave forecasting is already in place for the Great Barrier Reef, the new Australia-wide system will help environment managers anticipate and plan for damaging events in other sensitive areas and guide site selection for future marine protected areas.

Industry, Science and Technology Minister Karen Andrews said the warning system, announced during National Science Week, showed Australia was a “world-leading contributor when it comes to marine heatwave work”.