ANÁLISIS DE ESTRÉS Y SINTOMATOLOGÍA EN PECES MEDIANTE SISTEMAS DE VISIÓN ARTIFICIAL: UNA REVISIÓN DEL ESTADO DE ARTE (A STRESS ANALYSIS AND SYMPTOMATOLOGY IN FISH THROUGH ARTIFICIAL VISION SYSTEMS: A STATE-OF-THE-ART REVIEW)
Resumen
En este artículo se presenta una revisión del estado del arte exhaustiva enfocada a la aplicación de sistemas de visión artificial para el análisis de estrés y sintomatología en peces bajo condiciones de crianza. El estrés en los peces es una adaptación evolutiva que les permite hacer frente a cambios en su entorno. Puede ser causado por diversos factores que pueden afectar su desarrollo en condiciones de crianza.
La presente revisión analiza los distintos métodos encontrados en la bibliografía para evaluar el estrés en peces utilizando métodos no invasivos con técnicas de visión artificial. Se llevó a cabo una búsqueda exhaustiva en bases de datos como PubMed, IEEE Xplore y Scopus, identificando estudios entre 2012 – 2022 relacionados con el uso de sistemas de visión artificial en la evaluación de estrés y sintomatología en peces. Se utilizaron palabras clave relevantes, como "visión artificial", "análisis de comportamiento", "estrés en peces" y "bienestar animal", para seleccionar aquellos estudios que presentaran métodos y resultados sobre el uso de esta tecnología en entornos de crianza reales. Los estudios demuestran que la visión artificial es efectiva para analizar el estrés en peces, lo que puede beneficiar la conservación de poblaciones acuáticas, aunque se necesita más estandarización en las metodologías y datos más diversos para validar y generalizar los resultados.
Palabras Clave: Acuacultura, Estrés en peces, Visión artificial.
Abstract:
This article provides a comprehensive state-of-the-art review focused on the application of artificial vision systems for the analysis of stress and symptoms in fish under breeding conditions. Stress in fish is an evolutionary adaptation that enables them to cope with changes in their environment. It can be caused by various factors that can affect their development under breeding conditions.
This review examines the various methods found in the literature for assessing stress in fish using non-invasive techniques with artificial vision. A thorough search was conducted in databases such as PubMed, IEEE Xplore, and Scopus, identifying studies from 2012 to 2022 related to the use of artificial vision systems in the assessment of stress and symptoms in fish. Relevant keywords such as "artificial vision," "behavior analysis," "fish stress," and "animal welfare" were used to select studies that presented methods and results on the use of this technology in real breeding environments. The studies demonstrate that artificial vision is effective in analyzing stress in fish, which can benefit the conservation of aquatic populations, although more standardization in methodologies and a broader range of data are needed to validate and generalize the results.
Keywords: Artificial vision, Aquaculture, Fish stress.
Texto completo:
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