As electricity demands increase and grid reliability becomes more critical, E.ON Energidistribution, one of Sweden’s largest utility companies (E.ON) sought a safer and more efficient way to inspect their power lines. 
Traditional inspection methods were time-consuming, limited in scope, and often reactive. They needed a solution to analyze vast amounts of drone-captured data, prioritize defects, and support a strategic shift towards preventive maintenance

Background

E.ON Sweden transitioned from helicopter-based inspections to drone-based data capture, prioritizing sustainability and safety. However, this shift created a new challenge: the volume of visual data grew exponentially, demanding an efficient way to organize, analyze, and manage it. In their previous process, data collection was mostly manual and generated only limited information on immediate issues. With drones, E.ON now had comprehensive data, presenting a new requirement to harness the full value of this information.

Solution

To address this, E.ON implemented Arkion’s AI-powered asset analytics, which streamlined the analysis process and added automation to their data workflows. Drone operators now upload inspection data directly to Arkion’s platform, where analysis begins immediately. This approach made the insights accessible to E.ON in real-time, allowing them to detect and verify more issues with accuracy, all without the need for additional field visits.

“Arkion has helped E.ON to take power grid maintenance from 
the 1990’s to the 2030’s” - Christian Roos, Director of  New Connections and Services

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E.ON’s new process

Arkion’s analysis covered E.ON’s entire grid and integrated directly with their asset management system (AMS). This integration not only enhanced maintenance planning but also enriched E.ON’s asset database by identifying assets that were previously mislabeled or incorrectly placed in the system.

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1Data is uploaded directly to Arkion by the drone pilots and any apparent critical issue is reported directly. 2Arkion initiates automatic AI-powered analysis. All visual data is automatically sorted and made available to E.ON.3Results undergo quality assurance by Arkion. The results are available to E.ON within days.4E.ON extract insights and plan maintenance using the Arkion platform. Data integrates into E.ON’s asset management system for long-term records and work orders.

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“Arkion has enabled us not only make the right decision right now, but more importantly we can make the right long-term decisions to improve the reliability and availability of our grid.” - Jessica Krook, Director Local Grid & Businesses

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Key Features

1 Visualization and planning platform Get a visualization of your grid that’s easy to search, filter, and act on—delivered as structured data. We analyze it all, using our AI computer vision technology, validated by our in-house quality assurance team.Integrations to asset management

2 Arkion connected directly to E.ONs central Asset Management System (AMS) to improve data quality and simplify the work order creation process from defect detection to field trip.

3 AI-powered defect detectionSort and filter Arkion’s findings to see what’s at risk, and set priorities for maintenance and upgrades. Inspect cracked insulators, vegetation infringements, corrosion, and over 100 other issue types.

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Use cases

Maintenance Smarter decisions, fewer outages

With Arkion’s analysis, E.ON optimizes maintenance planning—shifting from time-based to condition-based strategies. This enables faster, more precise decisions on repairs and replacements, reducing risks and enhancing grid resilience.

Vegetation Proactive risk mitigation

By leveraging automatic LiDAR analysis using Arkion’s rule engine, E.ON detects vegetation risks early—preventing outages, minimizing damage, and accelerating recovery, all while making vegetation management more efficient.

Asset inventory A complete, precise asset overview

E.ON transforms standard condition assessments into structured, geo-referenced asset data—seamlessly integrated into their asset management system for improved accuracy and reliability, without additional investment.

Grid optimization Moving from models to facts

E.ON replaces assumptions with real-world insights, using Arkion’s asset analytics to prioritize grid upgrades and investments based on actual conditions.This long-term decision making helps increase the capacity of the whole grid.

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Results and Impact

The impact of reliable, accurate and structured physical asset data in E.ON’s processes has been massive. The immediate maintenance and vegetation impact wasn’t the only value. Besides enabling sustainable use of drone data capture and improving short-term maintenance needs, greater understanding has started to impact their long-term grid optimizations.

Short-term

‍E.ON identified up to 8 times more critical defects compared to their previous methods, significantly increasing their maintenance effectiveness and enabling a proactive approach to grid health. This enabled up-to 8 times more fixes per field visit.

Long-term

Within two years, E.ON achieved a return on investment (ROI) for the project. Beyond immediate efficiency gains, Arkion’s analytics provided valuable trend insights, enhancing E.ON’s ability to plan for the future and make data-driven, long-term decisions for grid reliability and safety.

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