Can AI and Machine Learning help us protect the natural world?

Keen AI, specialists in Machine Learning and Computer Vision, have partnered with leading environmental research organisation, the Centre for Ecology & Hydrology (CEH). Together they are planning to transform the management of natural assets with Artificial Intelligence (AI) and Machine Vision.

Both Keen AI and CEH are delighted at the prospect of utilising AI to better understand, manage and protect our natural world. Avid beekeeper and Founder CEO of Keen AI, Amjad Karim initially contacted CEH to see if Keen AI could help track the spread of the Asian Hornet (a damaging invasive species) across the UK by identifying it in images sent in by members of the public. He said:

When I spoke to CEH, it quickly became obvious that Machine Learning, and Machine Vision in particular, has great potential to augment CEH’s activities across the board. By using ML at scale we can uncover insight previously implicit but hidden in the large data sets and collections of images curated by CEH. Given the challenges we are currently facing, responsibly managing the natural world and presenting trusted sources of data to the public in general, this is a great thing.” 

Following the big-data trend, the use of meaningful AI applications is fast gaining traction. Together with Keen AI, CEH is seeking to drive the use of Machine Vision in the preservation and maintenance of natural ecosystems and the environment.

Tom August, a computational ecologist at CEH says, “New technologies such as Machine Vision offer exciting opportunities for our science. During our discussions with Keen AI it has become clear to us that the images we hold of UK wildlife can be used to create Machine Vision tools that can help create a better understanding of our biodiversity for businesses, government and members of the public.”

The curious case of Japanese Knotweed.‍

Japanese knotweed was originally grown in gardens in the UK as an ornamental plant. It is likely that from here it spread to adjacent areas such as railway lines, and from railway lines to other properties. Japanese Knotweed is now seen as an invasive species as its deep root system can damage walls and buildings.

Rail infrastructure operators could use our AI model to identify Japanese Knotweed, to map its extent and prevent future problems.    

Dr. Will Koning, Co-Founder at Keen AI told us: “We set up Keen AI to harness the power and efficiencies of machine learning to greatly expand what organisations consider routine inspection; ensuring issues can be identified years in advance. In addition to saving time and money from well-managed assets, the inspection process itself costs less while being faster and more comprehensive”.

The partnership will begin with a vegetation identification project. By collecting and labelling thousands of images of the UK’s flora and fauna through CEH’s citizen science projects, naturalists in the UK are helping to build a rich and diverse bank of data for use in training machine learning models. These models can then be used  to  accurately identify species from new images.

About CEH

CEH is a world-class research organisation focusing on land and freshwater ecosystems and their interaction with the atmosphere. They combine their wide-ranging areas of research to monitor environmental change, its drivers and  develop solutions for a sustainable future.

About Keen AI

Keen AI is a technology company specialising in Machine Learning and Machine Vision. They work with organisations and businesses to automate or augment processes using their KAI-Vision platform.

To learn more about the project, get in touch via the contact form.

About Will Koning

Will is responsible for research at Keen AI and business development in the Asia Pacific region. Will is an experienced leader in the field of data science, data analytics, integration, mathematical modelling, AI, machine learning and data-driven strategy consulting.

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