Artificial intelligence to ensure an efficient and sustainable future for recreational fisheries

• Recreational fishing is an activity that involves a significant number of people worldwide. According to FAO data, in countries where recreational fishing is common, the average percentage of the population participating in it is 6.7% — totaling more than 174.5 million individuals — resulting in significant economic and social impacts. In the Mediterranean, recreational fishing represents approximately 10% of total fisheries production. Despite its importance, this practice lacks a precise control system, leading to a lack of specific and reliable data essential for designing sustainable management of aquatic resources.

Researchers at the Mediterranean Institute for Advanced Studies (IMEDEA) have announced the development of an innovative monitoring system based on cameras and artificial intelligence that redefines local marine recreational fishing planning.

This system, focusing on the use of high-definition cameras and state-of-the-art computer vision algorithms, including deep learning, provides a revolutionary solution for data collection and efficient management of recreational fishing. It offers a unique combination of precision, automation, and scalability in real-time and at low cost, with minimal human intervention, making it particularly suitable for addressing the challenges associated with recreational fishing management.

The system can recognize and classify objects as recreational fishing boats, distinguishing between motorboats and sailboats, facilitating the study of the spatial distribution of different vessels.

To achieve advancements, the team has relied on time-lapse photography — extracted from high-definition cameras — and state-of-the-art computer vision algorithms, including deep neural networks or Deep Learning, techniques that detect and process visual information to classify and automatically obtain precise trajectories of vessels in coastal areas.

"These techniques are being applied to achieve significant advances in various scientific fields, including marine ecology and, consequently, in marine reserve management," explains Dr. Arancha Lana, technician at IMEDEA's Data Lab service and one of the study's signatories. "Our system not only contributes to the automatic surveillance of marine protected areas but also allows determining the intensity and space-time distribution of recreational fishing effort. This information is crucial for defining the sustainability of activity in coastal areas. Additionally, recreational fishing can have significant impacts on the sustainability of coastal fish populations, making it crucial to implement tailored strategies for their management and monitoring," concludes Lana.

Monitoring and tracking of marine protected areas: essential to ensure the achievement of Sustainable Development Goals for life under the sea.

The implementation of this system could mark a milestone in the management and conservation of marine biodiversity, preventing the overexploitation of fish populations targeted by recreational fishing. This technological advancement not only contributes to the sustainable development of recreational fishing but also aligns with the priorities of the European Maritime and Fisheries Fund and the Common Fisheries Policy to improve scientific understanding of marine recreational fishing.

Why does this technology represent a revolutionary change for data collection and efficient management of recreational fishing?

Reference:

Marco Signaroli, Arancha Lana, Josep Alós

"Novel computer vision tools applied to marine recreational fisheries spatial planning"