Discover Wematics

Discover Wematics

Discover Wematics

Wematics is redifining solar power forecasting with AI-driven fisheye sky camera devices. Introducing SkyAI and SkyTwin - setting new standards in cloud visualization and solar energy predictions.

Wematics is redifining solar power forecasting with AI-driven fisheye sky camera devices. Introducing SkyAI and SkyTwin - setting new standards in cloud visualization and solar energy predictions.

SkyAI: Compact and versatile Sky camera

SkyAI: Compact and versatile Sky camera

Built on the pillars of deep learning and edge AI, SkyAI is our solution for solar monitoring and forecasting. By reducing uncertainties, we empower grid operations to be more efficient and environmentally friendly.

Built on the pillars of deep learning and edge AI, SkyAI is our solution for solar monitoring and forecasting. By reducing uncertainties, we empower grid operations to be more efficient and environmentally friendly.

SkyTwin: A Virtual Co-Pilot for Real-Time Cloud Dynamics

Experience the first digital twin of the sky, our tech in volumetric cloud rendering and cloud shadow projection generates real-time irradiance maps for unparalleled performance.

Experience the first digital twin of the sky, our tech in volumetric cloud rendering and cloud shadow projection generates real-time irradiance maps for unparalleled performance.

MovingClouds - Dataset for Solar Nowcasting

About us


Wematics converged through a common vision, each deeply involved in sky camera R&D. Together, they're driving innovation in the sky camera tech space.


Max Aragon


CEO

Max


CEO

Max Aragon

CEO

Max Aragon

CEO

Max Aragon

CEO

Quentin Paletta

CIO

Quentin Paletta


CIO

Paul


CTO

Paul Matteschk


CTO

Paul


CTO

Paul Matteschk

CTO

Research


Advances in Solar Forecasting: Computer Vision with Deep Learning

Quentin Paletta, Guillermo Terrén-Serrano, Yuhao Nie, Binghui Li, Jacob Bieker, Wenqi Zhang, Laurent Dubus, Soumyabrata Dev, Cong Feng

SkyGPT: Probabilistic Short-term Solar Forecasting Using Synthetic Sky Videos from Physics-constrained VideoGPT

Yuhao Nie, Eric Zelikman, Andea scott, Quentin Paletta, Adam Brandt

Omnivision forecasting: Combining satellite and sky images for improved deterministic and probabilistic intra-hour solar energy predictions

Quentin Paletta, Guillaume Arbod, Joan Lasenby

Open-source ground-based sky image datasets for very short-term solar forecasting, cloud analysis and modeling: A comprehensive survey

Yuhao Nie, Xiatong Li, Quentin Paletta, Max Aragon, Andea scott, Adam Brandt

Sky-image-based solar forecasting using deep learning with multi-location data: training models locally, globally or via transfer learning?

Quentin Paletta, Anthony Hu, Guillaume Arbod, Philippe Blanc, Joan Lasenby

Cloud Flow Centring in Sky and Satellite Images for Deep Solar Forecasting

Quentin Paletta, Guillaume Arbod, Joan Lasenby

SPIN: Simplifying Polar Invariance for Neural networks Application to vision-based irradiance forecasting

Quentin Paletta, Anthony Hu, Guillaume Arbod, Philippe Blanc, Joan Lasenby

ECLIPSE: Envisioning CLoud Induced Perturbations in Solar Energy

Quentin Paletta, Anthony Hu, Guillaume Arbod, Joan Lasenby

Benchmarking of Deep Learning Irradiance Forecasting Models from Sky Images - An in-depth Analysis

Quentin Paletta, Guillaume Arbod, Joan Lasenby

A Temporally Consistent Image-based Sun Tracking Algorithm for Solar Energy Forecasting Applications

Quentin Paletta, Joan Lasenby

Stereo cloud base height estimation using a pair of all-sky cameras

Max Aragon

Ground-based cloud analysis for potential assimilation in high-resolution NWP models

Max Aragon

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