The startup develops a data intelligence platform that utilizes proprietary algorithms to analyze raw data from wind turbine blade-condition assessments and wind farm management systems. This technology provides actionable insights that help customers extend blade life, improve turbine performance, and mitigate revenue loss due to maintenance issues.
Funding
$750K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Wind turbine blades are susceptible to damage from environmental factors, leading to decreased energy production and potential revenue loss for wind farm operators. Traditional inspection methods are often manual, time-consuming, and can be inconsistent, making it difficult to detect early-stage damage and optimize maintenance schedules.
Solution
EdgeData provides a data intelligence platform, BladeEdge, that leverages proprietary algorithms and image-based autonomous AI (EDDIE) to analyze data from wind turbine blade inspections and wind farm management systems. The platform transforms raw inspection data, often gathered via drone-based aerial surveys, into actionable intelligence. By automating blade condition assessments and flagging maintenance issues, BladeEdge enables proactive blade management, extends blade life, enhances turbine performance, and mitigates revenue loss. The system stitches together hundreds of inspection photographs to create a single, high-resolution mosaic of each blade, providing a comprehensive view of blade conditions.
Target Audience
The primary target audience includes wind farm operators, maintenance teams, and inspection service providers seeking to improve turbine efficiency, reduce maintenance costs, and extend the lifespan of their wind turbine blades.
Features
- Image-based autonomous AI (EDDIE) processes inspection data with high accuracy
- Streamlined software for UAV operators ensures comprehensive data capture in the field
- Automated blade condition assessments identify wear and damage
- Automatic flagging of maintenance issues for early detection
- High-resolution mosaic view of each blade created from stitched inspection photographs
- Smart database tracks turbine conditions over time, leveraging AI to automate maintenance cycle planning
- Online interactive portal transforms raw data into actionable intelligence