About
FP Aqua is a marine technology company transforming water management through AI-powered sensor systems and advanced data analytics. At the core of their offering is the PlanktonSensor V4™, an underwater microscope combined with machine learning models that continuously detect and classify microscopic threats — including harmful algal blooms, micro-jellyfish, and invasive planktonic species — in real time. Designed for aquaculture operators, coastal regulators, and marine researchers, FP Aqua addresses the growing challenge of invisible aquatic threats driven by climate change and nutrient runoff. By identifying organisms before they cause visible damage, the platform enables proactive interventions that reduce fish mortality, lower treatment costs, and support healthier marine ecosystems. The system provides continuous real-time monitoring that feeds into interactive web portals and dashboards via simple API integration. All AI-based species identifications are validated by marine biologists at the PhD level, ensuring scientific accuracy alongside automated speed. The technology is built to scale with advances in AI, camera, and sensor hardware, and is designed for energy efficiency with minimal environmental impact. Key use cases span salmon and fish farm management, coastal biosecurity surveillance, open-water infrastructure monitoring, and freshwater ecosystem research. FP Aqua has conducted prototype testing with major aquaculture partners including Mowi and Bjørøya, as well as academic institutions such as DTU Aqua.
Key Features
- PlanktonSensor V4™: An underwater microscope with advanced AI models that continuously detects and classifies planktonic organisms including harmful algae and micro-jellyfish in real time.
- Real-Time Continuous Monitoring: Provides uninterrupted water column surveillance, enabling early warnings and timely preventative action before threats become visible problems.
- API & Dashboard Integration: Simple API integration connects sensor data to interactive web portals and dashboards, fitting seamlessly into existing operational reporting workflows.
- PhD-Validated AI Identifications: All AI-based species classifications are verified by marine biologists with PhD-level expertise, combining automation speed with scientific rigor.
- Scalable AI Architecture: Built to evolve with future advances in AI, machine learning, camera technology, and sustainable materials without requiring full system replacement.
Use Cases
- Aquaculture farm operators monitoring for harmful algal blooms and micro-jellyfish to protect fish stocks and reduce emergency treatment costs.
- Coastal and government biosecurity agencies detecting invasive aquatic species before they establish and spread in new environments.
- Open-water infrastructure managers tracking fine-scale planktonic activity across large maritime areas for safety and operational planning.
- Marine research institutions conducting continuous, long-term studies on plankton population dynamics, ocean health, and climate change impacts.
- Freshwater ecosystem managers monitoring lakes, rivers, and reservoirs for early signs of ecological disruption caused by harmful organism blooms.
Pros
- Early Threat Detection: Detects harmful organisms at microscopic scale before visible damage occurs, enabling proactive management that can save millions in fish loss and treatment costs.
- Scientifically Validated Outputs: AI identifications reviewed by PhD marine biologists ensure high accuracy and scientific credibility for regulatory and research applications.
- Seamless Data Integration: API-first design allows easy embedding of monitoring data into existing aquaculture management platforms and operational dashboards.
Cons
- Hardware Dependency: Requires physical deployment of underwater sensor hardware, which involves installation, maintenance, and potential logistical challenges in remote or offshore locations.
- Enterprise-Focused Pricing: As a specialized B2B solution targeting aquaculture operators and government agencies, the platform is likely cost-prohibitive for small-scale or independent researchers.
- Limited Public Documentation: Detailed technical specifications, pricing tiers, and integration documentation are not publicly available, requiring direct contact for evaluation.
Frequently Asked Questions
What is the PlanktonSensor V4™ and how does it work?
The PlanktonSensor V4™ is an underwater microscope combined with AI and machine learning models. It is deployed in water bodies and continuously captures images of microscopic organisms, which the AI classifies in real time to identify harmful species like algae and micro-jellyfish.
Who is FP Aqua designed for?
FP Aqua is designed for aquaculture operators (such as salmon farms), marine biosecurity authorities, coastal managers, and ocean researchers who need continuous, automated insight into water quality and planktonic threats.
How does FP Aqua integrate with existing systems?
The platform offers a simple API that connects real-time sensor data to interactive dashboards and web portals, allowing it to integrate directly into your existing operational and reporting tools.
How accurate are the AI species identifications?
All AI-based identifications are validated by marine biologists at the PhD level, combining the speed of automation with the scientific rigor required for regulatory and research-grade reporting.
What environmental conditions can the sensor operate in?
The PlanktonSensor V4™ is designed for deployment across coastal, open-water, and freshwater environments. It is built for energy efficiency with minimal environmental impact, and the system architecture is designed to scale with future hardware advancements.
