%0 Journal Article 
%A Precioso Garcelán, Daniel
%T Applications of machine learning and data science to the blue economy sustainable fishing and weather routing
%D 2023
%U http://hdl.handle.net/10498/29451
%X The Blue Economy encompasses an interdisciplinary field of study aimed at achieving
sustainable utilization of ocean resources while preserving the environment’s health. The
importance of this concept lies in its role in achieving the Sustainable Development
Goals defined by the United Nations. Nevertheless, the pursuit of economic development
can often conflict with the principles of sustainability, underscoring the necessity of
leveraging adequate tools to address these challenges.
Data science, and particularly Machine Learning, has become a valuable tool
for addressing the challenges of the Blue Economy. For example, in the field of
sustainable fishing, monitoring fish populations is highly relevant and can be achieved
through Machine Learning models. In another area, such as maritime transport, the
implementation of weather routing tools can optimize sea routes, improving fuel
efficiency and ensuring a reduction in greenhouse gas emissions.
This thesis will delve into the study of sustainable fishing and weather routing in the
context of the Blue Economy, applying data science techniques to improve efficiency and
sustainability in both fields

%K Data Science
%K Machine Learning
%K Blue Economy
%K Sustainable fishing
%K Echo-sounder buoys
%K Weather routing
%K Ciencia de Datos
%K Economía Azul
%K Pesca sostenible
%K Boyas con ecosonda
%~ Universidad de Cádiz