Is the vessel fishing? Discrimination of fishing activity with low-cost intelligent mobile devices through traditional and heuristic approaches
Knowing the activity of fishing vessels accurately and in real time means a leap in quality in the management of fishing activity. This paper presents the development of a new fishing activity monitoring integral system (FAMIS) that can complement and overcome the limitations of current fishing vess...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad de Huelva (UHU) |
| Repositorio: | Arias Montano. Repositorio Institucional de la Universidad de Huelva |
| Idioma: | inglés |
| OAI Identifier: | oai:ariasmontano.uhu.es:10272/21267 |
| Acceso en línea: | http://hdl.handle.net/10272/21267 |
| Access Level: | acceso abierto |
| Palabra clave: | Vessel monitoring system Mobile device Sensor Trawl fishing Ship’s behavior Machine learning 31 Ciencias Agrarias |
| Sumario: | Knowing the activity of fishing vessels accurately and in real time means a leap in quality in the management of fishing activity. This paper presents the development of a new fishing activity monitoring integral system (FAMIS) that can complement and overcome the limitations of current fishing vessel monitoring systems (VMS). FAMIS is developed on the basis of a low-cost mobile device with GPS sensors, accelerometer, gyroscope and magnetic field and integrates different statistical methods (discriminant functions) and heuristics (artificial neural networks and vectorial support machines) as techniques to classify the information recorded by the sensors of a mobile device during fishing activity. The results obtained with FAMIS indicate that, in general, heuristics have a high degree of discrimination of each of the phases of fishing operation and that, in particular, multilayer perceptrons (MLPs) are capable of correctly identifying 96.3% of towing phases using only GPS and gyro sensors. |
|---|