Hello Axelera AI Community!
I'd like to participate in The Prompt Challenge with a project called AquaRov AI.
Marine aquaculture is one of the fastest-growing food industries, but underwater monitoring is still largely performed manually. Fish farmers often face problems such as damaged nets, poor water quality, fish disease, biofouling, and fish mortality before they are aware of the issue. These problems reduce productivity and increase operational costs.
My goal is to build AquaRov AI, an Edge AI-powered underwater monitoring system using an ROV (Remotely Operated Vehicle), underwater cameras, and environmental sensors running on Axelera Metis.
The system will continuously inspect fish cages and analyze underwater conditions in real time. Instead of only recording video, AquaRov AI will use AI to understand what is happening underwater.
The AI system will be designed to:
Detect damaged or torn fish nets.
Detect dead or unhealthy fish.
Monitor fish behavior.
Detect excessive biofouling on fish cages.
Monitor underwater visibility.
Analyze environmental sensor data.
Send real-time alerts when abnormal conditions are detected.
Running AI directly on Axelera Metis will enable low-latency inference without relying on cloud computing. This is especially important because many offshore fish farms have unreliable internet connectivity.
Voyager Wingman will play an important role in accelerating development. I plan to use it to generate AI pipelines for underwater object detection, fish behavior analysis, environmental monitoring, video processing, and deployment on Axelera Metis. This will allow rapid development during the four-week challenge.
Beyond fish farming, the same platform could be adapted for coral reef monitoring, offshore infrastructure inspection, marine environmental protection, and scientific research.
Indonesia is one of the world's largest maritime nations, yet many aquaculture operations still depend on manual inspection. I believe Edge AI can make underwater monitoring more efficient, more affordable, and more sustainable.
If selected, I hope to demonstrate how Axelera Metis and Voyager Wingman can power practical Edge AI solutions for real-world marine applications.
Thank you for reading, and I look forward to your feedback.
