Project Solar

Sector

Recursive-built AI for energy and environmental application

Type

ML

AI Type

Custom Machine Learning Models (ML)

Project Delivered

2023

DATA ANALYSISHYBRID MODELSWEATHER MODELLINGDATA PREPROCESSINGPHYSICS INSPIRED NEURAL NETWORK

AI-powered system for accurate solar energy forecasting and site optimization.

We developed a hybrid AI and physics-based model that predicts solar radiation and power output with up to 96% accuracy. It helps renewable energy providers optimize site selection, improve panel performance, and reduce investment risks.

"The combination of an engineering viewpoint and expertise in biophysics was a tremendous asset and a great source of reassurance."

Takeshi Kato

Chief Engineer Environment and Resources Division, Sumitomo Forestry

"The combination of an engineering viewpoint and expertise in biophysics was a tremendous asset and a great source of reassurance."

Takeshi Kato

Chief Engineer Environment and Resources Division, Sumitomo Forestry

"The combination of an engineering viewpoint and expertise in biophysics was a tremendous asset and a great source of reassurance."

Takeshi Kato

Chief Engineer Environment and Resources Division, Sumitomo Forestry