WindSmart
Boost Wind Farm Efficiency with Predictive Maintenance
Meet
WindSmart
STORY
WindSmart was founded with the goal of improving wind farm efficiency through predictive maintenance technology. Our team of data scientists and engineers are committed to helping wind farms reduce costs and increase productivity.
VISION
At WindSmart, our vision is to be the leading provider of predictive maintenance technology for wind farms. We strive to be at the forefront of innovation, continually improving our technology to better serve our clients.
TECHNOLOGY
WindSmart's predictive maintenance technology uses advanced data science techniques to analyze real-time data and accurately predict potential wind turbine failures. Our platform provides wind farm operators with clear and actionable insights, allowing for more efficient maintenance practices and improved wind farm performance.
TECHNOLOGY
01 / ACCURATE
WindSmart's predictive maintenance technology uses real-time data to accurately predict potential wind turbine failures. By identifying problems before they occur, we help wind farms plan preventative maintenance, avoiding expensive component replacements and minimizing production downtime.
02 / EFFICIENT
Our technology streamlines the maintenance process, allowing wind farms to proactively address potential issues. This results in more efficient maintenance practices and improved wind farm performance.
03 / USER-FRIENDLY
Our technology is user-friendly, providing wind farm operators with clear and actionable insights. WindSmart's platform is easy to integrate and use, making it a valuable asset for any wind farm operator.
PRODUCT PREVIEW: WIND TURBINE PERFORMANCE MONITOR
Meet the Team
We are a team of graduate students from the University of California, Berkeley's Master of Information and Data Science program. This product was built for our Capstone project as a culmination of our studies.
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Our team would like to extend a special thanks to our Capstone advisors Joyce Shen and Zona Kostic for their guidance and Thibaut Forest (Lead Data Scientist, Renewables - Equinor) for his domain-specific insights. This wouldn't have been possible without your support.