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AI Models to Help Identify Invasive Species of Plants Across the UK

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Environmental scientists and artificial intelligence researchers are utilizing AI to fight an invasive species spreading across the UK. Researchers from the UK Centre for Ecology and Hydrology (UKCEH) and Birmingham have developed an AI model intended to survey regions like roadsides for the presence of various invasive species, including Japanese knotweed.

Japanese knotweed is an invasive species that can do damage to natural landscapes and buildings around the UK, as it’s able to damage the foundations of buildings. It’s often considered one of the most damaging and aggressive invasive plant species in the UK. Getting rid of Japanese knotweed often proves challenging because it proves challenging to find and identify. AI researchers are hoping that the machine learning algorithms can cut down on the time and resources needed to identify Japanese knotweed.

Training data was collected for the model through the use of high-speed cameras placed on top of vehicles, which collected images of approximately 120 miles of vegetation on the roadside. Ecologists will examine the images and label the knotweed, and the images will have their GPS location tagged. The labeled images will then be used to train a computer vision model to recognize samples of Japanse knotweed. The same process will be used to recognize other species of invasive plants found in the UK, such as Himalayan balsam and rhododendrons. The system will also be used to detect ash trees, which are native to the UK but are at risk of being decimated by disease.

The AI model will be tested over the course of a 10-month pilot project. The research team says that there are challenges that the team needs to overcome, such as being sure that the images captured by the cameras are of consistent quality and that when there are multiple species in a single image all species are properly identified. If the pilot program ends up delivering promising results, it could end up being adapted for use in other countries around the globe, helping these countries battle their own invasive species problems. As computational ecologist at UKCEH,  Dr. Tom August, was quoted by The Next Web:

“Invasive plant species tend to grow in corridors, which is why we’re focused on roadside surveys a computational ecologist at UKCEH. If the pilot is successful, this could be scaled up in other countries, or for other species of plants, trees or even insects and animals.”

According to August, AI models open up many possibilities for learning about the natural world and engineering efficient, cost-effective solutions to invasive species. UKCEH is collaborating with Keen AI, an AI company based in Birmingham. The founder of Keen AI, Amjad Karim, was quoted by Science Focus as saying that the use of AI models to analyze images and detect invasive species can help reduce costs and provide safety to landowners, highway agencies, and policymakers. The primary method of gathering roadside images currently requires surveyors, and that road is temporarily closed while they complete their work.

The new project designed by UKCEH and Keen AI is just the latest in a growing trend that sees the application of AI to fight invasive species. Late last year, AI researchers from Microsoft and CSIRO joined forces to design an AI model that can an invasive species called para grass, found throughout Kakadu National Park in Australia. Para grass is a fast-growing weed that can spread rapidly, quickly displacing many native plants in a region. The researchers utilized images collected by drones, and once the model was trained on the labeled images it was able to successfully identify para grass, allowing the researchers to remove it from vulnerable wetlands. This had the effect of allowing thousands of magpie geese to return to the region. Yet another team of researchers from the New University of Alberta used machine learning models to design containment and mitigation strategies for various invasive species in Canada.

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Blogger and programmer with specialties in Machine Learning and Deep Learning topics. Daniel hopes to help others use the power of AI for social good.

Environment

AI Used to Monitor Health of Coral Reefs and Detect Ocean Trash Pollution

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Intel has recently partnered with Accenture and the Sulubaaï Environmental Foundation to create an AI-driven data collection platform aimed at analyzing and protecting vulnerable marine habitats, habitats like coral reefs.

A combination of climate change, pollution, and overfishing have been damaging the world’s oceans, particularly coral reefs. Coral reefs around the world are experiencing mass die-offs and problems like coral bleaching. Scientists and conservationists are looking for ways to protect coral reefs and help them recover. Designing plans to support coral reefs requires data, and as Engadget reported, Intel has partnered with two environmental foundations to create the  CORaiL platform. The purpose of CORaiL will be collecting information on coral reefs and other marine habitats, providing researchers with the data they need to determine what strategies could be effective at protecting vulnerable marine ecosystems. As Jason Michell, managing director of the Communications, Media, and Technology practice at Accenture explained in a blog post:

“Artificial intelligence provides unprecedented opportunities to solve some of society’s most vexing problems. Our ecosystem of corporate and social partners for this ‘AI for social good’ project proves that there is strength in numbers to make a positive environmental impact.”

In May of last year, the team of researchers and engineers from the three organizations installed concrete structures along reefs found near the Philippines’ Pangatalan Island. The concrete chunks contained sections of living coral capable of growing into new habitat for creatures inhabiting coral ecosystems. In addition, the researchers placed video cameras underwater  near the structures so they could collect data on the coral and the surrounding environment. The cameras utilized an AI-driven video analytics system developed by Accenture, and the cameras enabled the researchers to gather data on the reefs through minimally invasive methods.

Accenture’s AI video analytics system lets researchers collect real-time video data from the coral environments, without needing to be physically present in the water. While many divers collect footage of coral reefs, this incurs travel expenses and presents the possibility that the divers could interfere with wildlife in the area. The AI video platform does much of the data collection and analysis for the research teams, continually monitoring the environment for change, and letting researchers do analysis in more or less real-time.

Over the course of the past year, CORaiL has collected around 40,000 images for analysis, and the images are already helping researchers analyze how coral reefs change in response to shifting environmental conditions. Meanwhile, engineers from the cooperative effort are already working on the next generation of the CORaiL system. The next proptype will include a backup power supply and an optimized series of convolutional neural networks. New versions of CORaiL might be employed for tasks other than studying coral, such as studying how tropical fish migrate through cold waters or monitoring for violators of reef protection orders.

CORaiL isn’t the only new project to make use of AI with the goal of protecting the oceans. A new AI system designed by researchers from the Plymouth Marine Laboratory in the UK tracks plastic pollution in the ocean through the analysis of satellite imagery. The AI system analyzes imagery collected by the European Space Agency’s (ESA) satellites and finds large chunks of floating debris by analyzing the “spectral signature” produced by the trash (patterns of light absorbed and reflected by the trash). After training, the AI was able to recognize a multitude of different objects when tested on images of seas from Vietnam, Canada, Ghana, and Scotland. The AI reportedly achieved approximately 86% accuracy when differentiating trash from natural objects.

According to the scientists involved in the research, their experiment marks the first time that plastic pollution has been tracked with satellites. The research team wants to improve the technique and enable it to detect patches of trash within rivers and along coastal regions.

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Intel & Accenture Discuss Using AI to Save Coral Reefs – Interview Series

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We sat down (virtually) with Patrick Dorsey, the Vice President of Product Marketing, Programmable Solutions Group, Intel and Jason Mitchell, a managing director in Accenture’s Communications, Media & Technology practice and the company’s client lead for Intel.

We discussed how on Earth Day 2020, AccentureIntel and the Sulubaaï Environmental Foundation decided to partner to use artificial intelligence (AI) – powered solution to monitor, characterize and analyze coral reef resiliency in a new collaborative project called CORail.

On Earth Day 2020, project CORaiL was announced, what was it about this project that caused you to take notice?

Jason Mitchell: Coral reefs are some of the world’s most diverse ecosystems, with more than eight hundred species of corals building and providing habitats and shelter for approximately 25% of global marine life. The reefs also benefit humans — protecting coastlines from tropical storms, providing food and income for 1 billion people, and generating US$9.6 billion in tourism and recreation annually. But reefs are being endangered and rapidly degraded by overfishing, bottom trawling, warming temperatures and unsustainable coastal development.  This project allowed Accenture and our ecosystem partners to apply intelligence to the preservation and rebuilding of this precious ecology and measure our success in a non-intrusive way.

 

Could you describe some of the technology at Intel that is being used in the underwater video cameras?

Patrick Dorsey: The underwater cameras are equipped with the Accenture Applied Intelligence Video Analytics Services Platform (VASP) to detect and photograph fish as they pass. VASP uses AI to count and classify the marine life, with the data then sent to a surface dashboard, where it provides analytics and trends to researchers in real time, enabling them to make data-driven decisions to protect the coral reef. Accenture’s VASP solution is powered by Intel® Xeon® processors, Intel® FPGA Programmable Acceleration Cards, an Intel® Movidius™ VPU and the Intel® Distribution of OpenVINO™ toolkit.

 

Work is currently being undertaken on the next-generation CORaiL prototype. What advanced features will this prototype have compared to the current version of CORaiL?

Jason Mitchell: We are scaling our work in the Philippines with a next-gen Project: CORaiL prototype, which will include an optimized convolutional neural network and a backup power supply. We are also looking into infra-red cameras which will enable videos at night to create a complete picture of the coral ecosystem. These technology advances will allow our solution to scale to look at new use cases like: studying the migration rate of tropical fish to colder countries and monitoring intrusion in protected or restricted underwater areas.

 

Could you share some of the computer vision challenges that are involved in monitoring different fish populations in an underwater setting which may result in significant changes in lighting conditions?

Patrick Dorsey: A critical element of Project: CORaiL is to identify the number and variety of fish around a reef, which serve as an important indicator of overall reef health. Traditional coral reef monitoring efforts involve human divers manually capturing video footage and photos of the reef, which is dangerous and time-intensive and can disrupt marine life, as divers might inadvertently frighten fish into hiding.

 

CORaiL monitors coral reef health in the Philippines, are there plans on expanding to other regions?

Jason Mitchell: It’s still early days with this technology, so we’re currently focused on the reef surrounding the Pangatalan Island in the Philippines.

 

Is there anything else that you would like to share about CORaiL?

Jason Mitchell: AI should be an added contributor to how people perform their work, rather than a backstop for automation. For Project: CORaiL, AI is empowering our engineers to achieve more and learn faster when it comes to growing the coral reef.  It empowers the solution to gather data in a non-intrusive manner, allowing the scientists and data engineers to gather data from the reef with minimal disruption to this fragile ecology.

 

What are some of the other ways AI is being used for Social Good?

Patrick Dorsey: At Intel, we are working with partners to use AI to curb anti-poaching of endangered animals, to map vulnerable populations, to help the quadriplegic community regain mobility and more. We are deeply committed to advancing uses of AI that most positively impact the world.

Jason Mitchell: Through our Responsible AI practice at Accenture, we help organizations implement governance frameworks and tools to ensure they’re deploying AI in a way that aligns to their corporate values and mitigates unintended consequences.

I would like to thank both of you for taking the time to explain why AccentureIntel chose to collaborate on this mission to save one of earth’s most precious resources. 

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Big Data

Accenture, Intel, & Sulubaaï Partner to Launch Project CORaiL to Save Coral Reefs

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Today, on Earth Day 2020, Accenture, Intel and the Sulubaaï Environmental Foundation announced Project: CORaiL, an artificial intelligence (AI) – powered solution to monitor, characterize and analyze coral reef resiliency.

Project: CORaiL was deployed in May 2019 to the reef surrounding Pangatalan Island in the Philippines and has collected approximately 40,000 images, which have been used by researchers to gauge reef health in real time.

“Project: CORaiL is an incredible example of how AI and edge technology can be used to assist researchers with monitoring and restoring the coral reef. We are very proud to partner with Accenture and the SulubaaÏ Environmental Foundation on this important effort to protect our planet.”

— Rose Schooler, Intel corporate vice president in the Sales and Marketing Group

Why it Matters

This study is important as coral reefs are among the world’s most vulnerable life forms, with more than 800 species of corals providing habitat and shelter for approximately 25% of global marine life.

Coral reefs are currently under assault with coral bleaching being a direct result of rising sea temperatures. Other causes of bleaching include changes to light, or nutrients in ocean waters. This forces the coral to expel symbiotic algae living in their tissues, which results in the white color that is most often associated with bleaching.

Coral reefs are also underappreciated and beneficial to the survival of humans. They protect coastlines from tropical storms, provide jobs and food for 1 billion people, and generate $9.6 billion in tourism and recreation each year.

“Artificial intelligence provides unprecedented opportunities to solve some of society’s most vexing problems,” said Jason Mitchell, a managing director in Accenture’s Communications, Media & Technology practice and the company’s client lead for Intel. “Our ecosystem of corporate and social partners for this ‘AI for social good’ project proves that there is strength in numbers to make a positive environmental impact.”

How Big Data & Machine Learning is Used

The abundance and diversity of fish serve as an important indicator of overall reef health. Traditional coral reef monitoring efforts involve human divers either directly collecting data underwater or manually capturing video footage and photos of the reef to be analyzed later. Those methods are widely trusted and employed, but they come with disadvantages: divers can interfere with wildlife behavior and unintentionally affect survey results, and time underwater is limited as divers can often only take photos and video for around 30 minutes.

Engineers from Accenture, Sulubaaï and Intel combined their expertise for Project: CORaiL to restore and supplement the existing degraded reef in the Philippines. First, they built a Sulu-Reef Prosthesis, a concrete underwater platform designed by Sulubaaï to provide strong support for unstable coral fragments. The Sulu-Reef Prosthesis incorporates fragments of living coral within it that will grow and expand, providing a hybrid habitat for fish and marine life. Then, they strategically placed intelligent underwater video cameras, equipped with the Accenture Applied Intelligence Video Analytics Services Platform (VASP) to detect and photograph fish as they pass. VASP uses AI to count and classify the marine life, with the data then sent to a surface dashboard, where it provides analytics and trends to researchers in real time, enabling them to make data-driven decisions to protect the coral reef.

Accenture’s VASP solution is powered by Intel® Xeon® processors, Intel® FPGA Programmable Acceleration Cards, an Intel® Movidius™ VPU and the Intel® Distribution of OpenVINO™ toolkit.

What’s Next

Engineers are at work on the next-generation Project: CORaiL prototype, which will include an optimized convolutional neural network and a backup power supply. They are also considering infrared cameras, which will allow for videos at night to create a complete picture of the coral ecosystem. Additional uses could include studying the migration rate of tropical fish to colder countries and monitoring intrusion in protected or restricted underwater areas.

We can only hope that this project is expanded in future jurisdictions which need to closely monitor coral reef health such as Australia, and the Caribbean. Both are some of the most vulnerable waters in the world due to the unforgiving nature of global warming.

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