Keen AI and CEH Combine their Expertise to Tackle Invasive Species

Keen AI, the UK Centre for Ecology and Hydrology (CEH) and Time-Lapse Systems are using their expertise in machine vision, environmental research and image capture to help identify invasive plant species in the UK. Together we are partnering on a project to quickly survey large areas for harmful and damaging plant species.

The Problem

Invasive Non-Native Species (INNS) are organisms introduced into areas outside their native region where they then threaten ecosystems. They are regarded as one of the top five threats to biodiversity worldwide (IPBES, 2019), as well as having significant economic impacts, with companies in various sectors such as transport and utilities spending considerable time and resources to identify and remove them. Current methods for identifying the presence of INNS rely on ecological surveys, which are time consuming and costly, especially within road and rail infrastructure. Keen AI, CEH and Time-Lapse Systems are combining their expertise in AI, INNS and image collection to provide a faster and more efficient method of conducting surveys of this kind.

Current solutions for surveying an area for INNS include sending ecologists to perform a manual survey, which is time-consuming and costly, or the manual review of photographs taken from high definition digital cameras attached to drones or planes. Using AI technology, our proposal would reduce the time it takes to conduct an ecological survey of this kind, producing cost and time savings for the customer, and providing location specific information to support decision-making and management actions.

Schematic of Survey Collection and Processing

Our Solution

Our vision is to develop an AI platform for detecting the presence of invasive plant species within linear infrastructure. This innovation will provide a rapid, high quality vegetation survey methodology, which will result in cost and time savings for our customers, and result in an increased understanding of market requirements for an AI innovation of this type. The project will have four key objectives:

  1. Collection of vegetation imagery of sufficient quality;
  2. Training of AI algorithms to identify INNS in the image dataset;
  3. Processing high volumes of images to locate INNS geospatially; and
  4. Evaluation of the AI model performance.

The use of AI to rapidly analyse vast amounts of collected imagery will deliver safety and cost benefits to linear infrastructure vegetation asset managers. Such work currently requires the temporary closure of roads to ensure the safety of surveyors. We estimate costs associated with this to be up to £5800 per week covering 50 miles. An ecologist supported by our system could remotely survey 120 miles (20 mph for 6 hrs) without road closures. This is a cost per mile of £9 vs. £116.

Japanese Knotweed can cause harm to surrounding vegetation and properties

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 platform to identify Japanese Knotweed, to map its extent and prevent future problems.

Why this Partnership?

Keen AI has expertise in providing AI solutions to companies such as National Grid, helping to streamline their visual condition assessment process. CEH have a long track record of research on invasive species and are pioneering image recognition services for Japanese Knotweed with the conveyancing sector. Time-Lapse systems are experts in capturing imagery for specialist applications. Our complementary experience, skills and resources provide an opportunity to develop a novel AI platform for detecting the presence of invasive species.

About Keen AI

We specialise in creating cutting-edge AI and systems that empower our customers to easily collect, share, and analyse critical data related to their assets, accurately assessing their condition and making informed predictions about their future state.

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 Time-Lapse Systems

Time-Lapse Systems have been offering the best in ultra high definition time-lapse and site monitoring solutions continuously, as true end-to-end specialists, since 2007.  As one of the longest established European providers, they’ve serviced hundreds of clients over thousands of projects.

To learn more about the project, get in touch via the contact form. Learn more about our Ecological Surveys Platform solution.

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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