Werover
About us
Werover specializes in providing AI and IoT solutions for predictive and preventive maintenance, as well as 24/7 health monitoring solutions for wind energy turbine blades. Werover understands the risks that come with operating in the wind energy industry and strives to provide Werover’s customers with the most efficient and innovative solutions to mitigate those risks.
By offering preventive maintenance services based on robust data collected from wind turbines, we aim to cultivate a more efficient and reliable energy infrastructure. Ultimately, our goal is to accelerate the transition towards renewable energy sources, addressing environmental concerns and reducing reliance on fossil fuels.
Address
Fahrenheitstr. 1
28359 Bremen
Germany
E-mail: info@werover.com
Phone: +90 530 9368496
Internet: www.werover.com
Bornova Str.
Karacaoğlan neighborhood, 9/4A, Bornova, Işıkkent, Öztim Business Center
35070 İzmir
Turkey
E-mail: balca.yilmaz@werover.com
Phone: +90 530 3860136
Internet: www.werover.com
1 Elmfield Park
Bromley, London Opia Accountancy LTD.
BR1 1LU London
United Kingdom
E-mail: balca.yilmaz@werover.com
Phone: +90 530 3860136
Internet: www.werover.com
Contact person:
Products & Services
Windrover is an AI-based health monitoring system designed for wind turbine blades, providing 24/7 health monitoring and up to 50% savings in repair costs through predictive maintenance. By utilizing acoustic sensors and machine learning algorithms, it detects early-stage damage, such as cracks, erosion, leading-edge issues, and icing. Equipped with built-in solar panels, it ensures continuous, autonomous remote monitoring. The plug-and-play hardware is built to withstand harsh onshore and offshore conditions. Windrover also offers accessible data through a user-friendly mobile app, allowing operators to monitor and respond to potential issues in real-time.
Windrover
Windrover is an AI-based health monitoring system designed for wind turbine blades, providing 24/7 monitoring and up to 50% savings in repair costs through predictive maintenance. By utilizing acoustic sensors and machine learning algorithms, it detects early-stage damage, such as cracks, erosion, leading-edge issues, and icing. Equipped with built-in solar panels, it ensures continuous, autonomous remote monitoring. The plug-and-play hardware is built to withstand harsh onshore and offshore conditions. Windrover also offers accessible data through a user-friendly mobile app, allowing operators to monitor and respond to potential issues in real-time.
