

Successfully Utilising Machine Learning and AI at a Transmission Operator
Amjad Karim reviews some of the important lessons we learned whilst implementing the KAI platform at the UK’s National Grid.
Identify and categorise assets
with over 95% precision.
Find broken fittings and
assets with ease.
Automatically process tower images for
corrosion and its spread.
Dive deep into your asset in a fully
navigatable 3D world.
Effortless data exploration
and report sharing.
Identify and categorise assets with over 95% precision.
Effortless data exploration and report sharing.
Find broken fittings and assets with ease.
Automatically process tower images for corrosion and its spread.
Dive deep into your asset in a fully navigatable 3D world.
Superconductor uses deep learning to extract objects of interest and data engineering to ensure this visual data is easily available to anyone who needs it.
Bespoke edge detection algorithms are used to identify regions of the image likely to contain steel and thereby separate background from tower.
Eliminated 25% of towers from the manual review process by marking them as clean.
We have developed a vehicle mounted solution for collecting high resolution imagery of roadside vegetation. AI is then used for detecting the presence of invasive plant species or Ash trees.
This provides a rapid, high-quality vegetation survey methodology, resulting in cost and time savings for our customers.
Knowing the types of habitat and plants alongside rail tracks is crucial for Network Rail.
We have deployed camera systems to the front of trains for collecting images. Superconductor analyses data gathered and presents an overview to NR staff.
Digitising networks requires an inventory of what’s installed and where. This could be done manually by reviewing historic images and video. With thousands of structures and millions of images this is an exhausting manual process but an ideal opportunity for digitalisation and a practical use case for AI.
We are working with customers to complete detailed asset inventories using millions of images.
Superconductor extracts key components from footage presenting them for review by a condition assessment engineer. Our models aim to extract over 50% of defects automatically.
Superconductor reduces assessment time by 66% and minimises unforeseen asset failure.
Amjad Karim reviews some of the important lessons we learned whilst implementing the KAI platform at the UK’s National Grid.
18k Videos over 10 Years weren’t Assigned to an Asset Our customer has been collecting
Britain’s 20,000-mile rail network requires reliable monitoring of lineside vegetation. Together with the UK Centre
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