International Research Initiative • 2026-2029

Resilient Aquaculture
Outbreak Management

Will prove that cost-effective, data-driven solutions can rival expensive, high-tech monitoring systems in aquaculture disease management

4-Year Project · Norway • Philippines • Indonesia · Led by NORCE

Transforming Aquaculture Disease Management

AQUAROM will rethink technology investment in aquaculture—demonstrating that strategic resource use, rather than higher spending, drives innovation and productivity. Like DeepSeek AI, which achieves strong performance with limited resources, we will prove that cost-effective, data-driven solutions can rival expensive sensor networks.

For Norway

Despite Norway's 5.4 million population producing 1.65 million metric tons of farmed fish annually with advanced monitoring systems, R&D spending has increased significantly yet productivity gains have stalled. High-cost sensor networks show diminishing returns on disease prevention. We will use back-testing validation with Norwegian datasets to prove minimal-sensor setups can match high-tech systems through AI-enhanced analytics.

For the Philippines

The Philippines produces 2.35 million metric tons of farmed fish, yet the sector remains decentralized with limited real-time monitoring. Disease outbreaks including white spot syndrome and seasonal fish kills cause major losses. We will conduct two seasonal field trials (3-4 months each) across 6-10 aquaculture sites to validate affordable, low-cost monitoring solutions with AI-driven early warning systems tailored to resource-limited settings.

Global Impact

By conducting field trials in the Philippines and cross-validating with Norwegian data through six integrated work packages (WP0-WP5), we will bridge the gap between resource-limited and high-tech aquaculture environments. Our interdisciplinary approach will combine sensor optimization, fish epidemiology, AI-driven predictive models, stakeholder co-creation, and knowledge transfer to create practical, globally scalable solutions.

Why AQUAROM?

❌ Current Reality

  • → Rising R&D investment shows diminishing returns on productivity gains
  • → High-density sensor networks create redundancy and excessive costs
  • → Data overload in high-tech settings, data scarcity in resource-limited farms
  • → Disease prediction tools remain inaccessible to small-scale operators

✓ AQUAROM Solution

  • → Strategic minimal-sensor configurations optimized for cost-effectiveness
  • → AI-driven predictive models achieving ≥80% accuracy with sparse data
  • → Field-validated in Philippines, cross-validated with Norwegian datasets
  • → Privacy-preserving analytics enabling secure multi-farm collaboration

Dive Deeper

Research Approach

Explore our methodology, objectives, and innovative solutions

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Team & Partners

Meet our international research team and collaborative partners

Meet the Team

Join Our Team

PhD and Master's positions available across three countries

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Interested in Collaboration?

We welcome inquiries about research partnerships, PhD/MSc opportunities, industry collaboration, and stakeholder engagement.

Project Contact

Jeanette G. Bayona

Iloilo State University of Fisheries Science and Technology

contact@aquarom.no

Opportunities

• PhD positions (3 available)
• Research collaborations
• Industry partnerships
• Stakeholder workshops