OPTIMAL for cOPernicus irrigaTION mAnagement tooLkit is a combination of state-of-the-art Machine Learning techniques that is designed to forecast environmental parameters which enable the delivery of irrigation needs intelligence.
Maritime transport plays a vital role in our global economy, but navigating the vast ocean can be challenging. The AI4Copernicus ODFuse4Ship project, led by our Ocean-tech start-up AMPHITRITE, is set to change that by harnessing the power of satellite dat...
The Lobelia Air project focuses on calibrating low-cost air quality sensors using AI techniques leveraging on EO derived AQ and meteorological data.
The aim of this project is to develop an AI-based service that assists livestock farmers decision-making by leveraging IoT and satellite imagery. The service is focused on optimizing the use of the available natural resources and reducing the negative eff...
Fertirec offers Nitrogen Recommendation services for four major crops (Wheat, Barley, Rapeseed, and Corn) at both the postcode and district levels. This service is available for customers in the European Union (EU) and the United Kingdom (UK).
The containerised application contains TFS, a Bayesian Optimization of the state-of-the-art AI, N-Beats. The TFS is one of the components of ESFA's AI. TFS Docker Image has been adapted to work with any kind of time series, from weather to Bitcoin prices ...
EO4NOWCAST is a containerized application that comprises: - a machine learning pipeline for the hourly prediction of the soild moisture based on the NDMI maps from Copernicus S2 and ground based precipitation; - a machine learning pipeline for the 5-min p...
EO4NOWCAST is a containerized application that comprises: - a machine learning pipeline for the hourly prediction of the soild moisture based on the NDMI maps from Copernicus S2 and ground based precipitation; - a machine learning pipeline for the 5-min p...
Environmental comfort takes a central role in the well-being and health of people. In modern industrial, commercial, and residential buildings, passive energy sources (such as solar irradiance and heat exchangers) and Heating, Ventilation and Air Conditio...
The main goal of this project is to make accurate forecasts on the network’s future behaviour, taking into account, among other topics, problems related to the increasing integration of Distributed Energy Resources in LV networks.
