For the past two years, UK infrastructure firm National Grid has been using six drones to monitor the health of its physical network, inspecting more than 7,000 miles of overhead cables across England and Wales.
The drones use still, video and infrared cameras to examine the steelwork, wear and corrosion of pylons, as well as faults like frayed cabling and damaged conductors.
National Grid is turning to machine learning to process the massive amount of data that the drones capture - as an aid to humans, rather than a replacement.
"[The AI] will determine the overall condition of the asset and whether it needs to be replaced or repaired. We are just developing this as a prototype. When we talk about digitisation it's real practical engineering-type stuff we're doing," said CEO John Pettigrew.
Like many other examples of process automation, National Grid's ML implementation aims to cut the amount of data that humans need to review.
The work on automation only began within the last few months. National Grid is working with UK-based Keen AI on the technology, and is now iterating on the system to achieve better results.
Innovations like ML technology and drones - supplied by DJI - are vital to the future of companies like National Grid, said Pettigrew. As part of a heavily-regulated industry, energy suppliers operate under price controls that limit how much they can earn from investments paid for by consumers.
Raj Samani, chief scientist and Fellow at McAfee, warned:
"As businesses start taking advantage of drone technology for support in day-to-day monitoring and other activities, it is important that they ensure that appropriate due diligence is taken, especially if national infrastructure is in question.
"Many drones are manufactured in a way that makes them relatively easy for criminals to compromise; for example, the use of unencrypted video feeds have allowed malicious actors to view video from military drones in the past."
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