L2M – AquaFishSense

AquaFishSense addresses the pressing issue of outdated and insufficient information available to fisheries, which impedes their ability to operate sustainably and efficiently. Fisheries face significant challenges due to the lack of real-time data on fish populations and aquatic habitats. This gap in information leads to overexploitation of marine resources, with approximately 34% of global fish stocks being overexploited or depleted. The absence of accurate and up-to-date mapping of fish locations results in operational inefficiencies, causing fisheries to waste time and resources on less productive areas. The root cause of these challenges is the reliance on traditional, imprecise data collection methods that fail to provide integrated, near-real-time insights. Fisheries often lack the tools to adapt to changing environmental conditions or to identify optimal fishing zones, which exacerbates overfishing and habitat destruction. This inefficiency not only threatens marine biodiversity but also impacts the economic sustainability of fishing operations. The inability to pinpoint productive fishing areas results in reduced catch efficiency and increased operational costs. Addressing these issues with advanced satellite and AI-driven solutions is crucial for enhancing fishing practices, improving sustainability, and supporting better management of marine resources.

Faculty Supervisor:

Masoud Mahdianpari

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Aquaculture and Fishing; Artificial Intelligence; Ocean Tech

University:

Memorial University of Newfoundland

Program: