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Author: Daniel Precioso

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-[BBVA Foundation](https://www.fbbva.es/) and [Agencia Estatal de Investigación](https://www.aei.gob.es/), in collaboration with [IE University](https://www.ie.edu/), promote this interdisciplinary project aimed at providing algorithms to calculate safe and optimized shipping routes for reduced fuel consumption and emissions, taking into account real time oceanographic and meteorological information. The necessary data will be collected from public repositories such as NOAA, Copernicus or HYCOM, and they include predictions for ocean currents, wind and waves. Detailed models will be built to estimate the fuel consumption and emissions of every vessel as a function of its characteristics (displacement, hull length, engine power), cruising speed and sea conditions (currents, waves and wind).
+[BBVA Foundation](https://www.fbbva.es/) and [Agencia Estatal de Investigación](https://www.aei.gob.es/), in collaboration with [IE University](https://www.ie.edu/) and [Universidad de Cádiz](https://www.uca.es/), promote this interdisciplinary project aimed at providing algorithms to calculate safe and optimized shipping routes for reduced fuel consumption and emissions, taking into account real time oceanographic and meteorological information. The necessary data will be collected from public repositories such as NOAA, Copernicus or HYCOM, and they include predictions for ocean currents, wind and waves. Detailed models will be built to estimate the fuel consumption and emissions of every vessel as a function of its characteristics (displacement, hull length, engine power), cruising speed and sea conditions (currents, waves and wind).
 
 This task involves both reviewing the vast literature on this subject and possibly fitting our own data driven models in case routes and consumption data become available. Next, optimization algorithms will be developed to find optimal routes and calculate fuel savings and estimated time of arrival (ETA) at the port destination. Profiting from better sea and weather conditions has been shown to save on average 3-7% of fuel. This is a challenging project whose success depends on the cross fertilization and cooperation between oceanographers, naval engineers, data scientists, mathematicians and software developers.
 
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+Proyecto financiado por MCIN/AEI/10.13039/501100011033 y por la Unión Europea NextGenerationEU/PRTR.
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