Universiti Tunku Abdul Rahman (UTAR)

UTAR’s project focuses on creating a low-cost, privacy-preserving precision aquaculture framework tailored for small- and medium-scale fish farmers in Malaysia. The innovation features a federated learning based recommender engine, which optimizes farm productivity while protecting data privacy. Additionally, the project incorporates a lightweight edge-cloud framework for real-time monitoring and decision-making to improve feed conversion ratios, water quality, and aquaculture species growth with minimal operational costs. ABIC funding will support the setup and testing of the federated learning platform, the development of IoT gateway devices, and field verification of these systems with local prawn farmers. In the next six months, UTAR will deploy the first edge-cloud one-box solution in aquaculture farms, enabling real-time monitoring and decision-making. In two years, the goal is to promote widespread adoption of this solution in rural and developing regions, boosting household incomes and transforming small- and medium-scale aquaculture operations.