RT doctoral thesis
T1 Applications of machine learning and data science to the blue economy sustainable fishing and weather routing
A1 Precioso Garcelán, Daniel
A2 Ingeniería Informática
K1 Data Science
K1 Machine Learning
K1 Blue Economy
K1 Sustainable fishing
K1 Echo-sounder buoys
K1 Weather routing
K1 Ciencia de Datos
K1 Economía Azul
K1 Pesca sostenible
K1 Boyas con ecosonda
AB The Blue Economy encompasses an interdisciplinary field of study aimed at achievingsustainable utilization of ocean resources while preserving the environment’s health. Theimportance of this concept lies in its role in achieving the Sustainable DevelopmentGoals defined by the United Nations. Nevertheless, the pursuit of economic developmentcan often conflict with the principles of sustainability, underscoring the necessity ofleveraging adequate tools to address these challenges.Data science, and particularly Machine Learning, has become a valuable toolfor addressing the challenges of the Blue Economy. For example, in the field ofsustainable fishing, monitoring fish populations is highly relevant and can be achievedthrough Machine Learning models. In another area, such as maritime transport, theimplementation of weather routing tools can optimize sea routes, improving fuelefficiency and ensuring a reduction in greenhouse gas emissions.This thesis will delve into the study of sustainable fishing and weather routing in thecontext of the Blue Economy, applying data science techniques to improve efficiency andsustainability in both fields
YR 2023
FD 2023
LK http://hdl.handle.net/10498/29451
UL http://hdl.handle.net/10498/29451
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 10-may-2026