Smart Aquaculture IoT System

Multimodal AI, LLM RAG, Hydrophone, Full-stack — In Progress

An intelligent multi-sensory aquaculture monitoring and management system developed at the ICCL Lab, VinUniversity & Trinity College Dublin. Funded by a $3,500 Student Research Grant.

Key Features:

  • Multi-sensory IoT node: water quality sensors, underwater cameras, and hydrophones
  • Multimodal AI framework fusing visual and acoustic data for feeding schedule optimization and water quality forecasting
  • LLM with Retrieval-Augmented Generation (RAG) integrated into a Web App for context-aware advisory services to farmers
  • Semantic communication (AquaSC) for efficient data transmission over IoT links

Technologies: Python, PyTorch, OpenCV, Hydrophone DSP, LLM/RAG, Arduino, Raspberry Pi, Full-stack Web

GitHub: AquaSense

References