The traditional approach to assessing the condition of infrastructure assets like spacers, insulator strings, or even corrosion on towers is time-consuming and difficult to manage effectively.
Although the use of footage and images has improved the process, collecting data is still expensive, difficult to share, and has created data bottlenecks and silos, impacting quality and consistency.
Thousands of hours of footage and countless images from multiple suppliers often build-up creating a backlog for small teams, due to the scale of the workload, with results offering limited insights.
AI Powered Condition Assessment
Detection of transmission assets on overhead lines using KAI
A powerful asset condition solution from AI and Machine Learning experts, Keen AI
Our solution uses KAI, our AI platform, which allows transmission operators to better schedule and manage resources and inventories, and ultimately reduce outages.
KAI provides a central repository for aggregating data from internal surveys and suppliers. Trained AI models are applied to all media, identifying assets and defective components and flagging them for reviewers.
KAI significantly reduces the time taken to process defective assets. This increases capacity and gives you complete control of all historical and current data via a single application.
How KAI Works
Result: Cost and Time Savings
Saving due to increased competition for CA contracts
% Towers screened out for corrosion on first run
Reduction in condition assessment costs
Features & Benefits
Our pioneering approach to condition assessment saves time and reduces costs, while increasing your capacity and control of your data.