“The minute you’re satisfied with where you are, you aren’t there anymore.” - Tony Gwynn

PROJECTS BGT Consulting Group

Business – Government - Technology

AI-METHOD: Intelligent Modelling from Earth Observation Data

The envisaged innovation of our company is the development, implementation, and commercialization of a local short-to-medium-term atmosphere forecasting Software-as-a-Service platform for climate and energy forecasting applications based on original self-learning modelling technologies from high-resolved space-based earth observation data maintained in a Big Data platform. For validating and realizing the full potential of the innovation a number of complex and specialized tasks have to be executed in preparation of full-scale implementation.


We have supported in the design and delivery of a Coordination and Support Action focused on building innovation resources and know-how in Intelligent Inductive Modeling for further development of current concepts and preparation of follow-up EU/ESA/national innovation and commercialization project proposals. This action was designed to complement resources, knowledge, and skills in order to further strengthen the competitive advantage of our client’s geo-forecasting solutions. Its offerings include high-resolution forecasting in climate, energy, agriculture, oceanography and health care, and the Big Data it uses in its proprietary software processing is provided by satellites. The company works with earth observation data to develop solutions for industrial and societal issues linked to climate and energy.

R&D Outcomes

Main R&D results from this project are: (i) concept development of a storage and query framework for satellite earth observation data in a geospatial big data platform, (ii) design, development and implementation of a sophisticated algorithm for probabilistic forecasting, (iii) design, development and implementation of an algorithm for adaptive forecasting of time processes based on probabilistic forecasts, and (iv) design and development of an algorithm for structural and parametric identification of poly-harmonic functions of optimal complexity.

Funding body:

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