Aquaculture is one of the fastest-growing food production sectors; however, it faces persistent challenges related to limited water availability, environmental degradation, and production instability caused by inadequate water quality management. To address these issues, the Water Integrated System and Analysis for Sustainable Aquaculture Generation Initiative (WISANGGENI) is proposed as an integrated framework designed to optimize water use, maintain ecological balance, and enhance the long-term sustainability of aquaculture systems. WISANGGENI integrates real-time water quality monitoring, intelligent water treatment, and data-driven decision support into a unified adaptive platform. The system employs Internet of Things (IoT) sensors to continuously monitor key parameters such as temperature, pH, and turbidity, combined with recirculating water and biofiltration technologies to reduce waste and recycle resources. In addition, computational intelligence techniques, including machine learning, fuzzy logic, and predictive modeling, are applied to analyze sensor data and support operational decisions. Fuzzy logic is specifically utilized to manage uncertainty in water quality assessment by converting imprecise sensor inputs into actionable responses, such as aeration control, feeding regulation, and early warning alerts. Through this integrated approach, WISANGGENI improves feeding efficiency, optimizes aeration, reduces disease risk, and lowers freshwater consumption, thereby supporting more resilient, efficient, and environmentally sustainable aquaculture practices.
Dewanto et al. (Thu,) studied this question.