Drone-based power asset inspection firm focuses on AI

Three and a half years ago, US-headquartered AirFusion launched its first product, a drone-based data analytics tool for power and telecom companies.

The firm now operates a windfarm inspection business primarily in Europe, and is currently developing a new inspection system for high-voltage power transmission lines.

But its development is not focused on the drone itself. Rather than attempting to compete in the data collection space, AirFusion says it chose to focus on data processing and has developed a system that it says can cross-correlate the data gathered by multiple drone-mounted sensors with a database of potential wind turbine damage cues.à‚  à‚ 

The firm doesn’t just aim to replace human inspection of power machinery with UAV inspection. It also wants to replace most human analysis of the data gathered by a drone with artificial intelligence.à‚ 

AirFusion’s offering includes what it calls ‘assistive AI’, which differs from ‘autonomous AI’. Chief strategy officer Kevin Wells says autonomous AI “seeks to take the human being out of the equation altogether” while assistive AI aims to remove “the bulk of the time a human would need to spend doing damage discovery and classification”.

Edward Mier, managing director for Europe, adds that the AI element of AirFusion’s software is crucial to the company’s goal of “making the analyst’s work 95 per cent more efficient”. And he says it’s also what differentiates the company from the competition.

“In most of the instances [of drone-based inspection firms] we’ve come across, the AI element is missing. Particularly if you talk about wind, I don’t think we’ve found anybody really who’s actually got an active AI capability.”

Kevin Wells, Chief Strategy Officer at Air Fusion, is a speaker at Electrify Europe.à‚ For more details click here.

This is an extract of a longer article that appears in the latest issue of PEi Magazine. To read the full article, subscribe at Power Engineering International magazine.à‚ 

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