IoT based Smart Water Quality Prediction for Biofloc Aquaculture
This addresses water quality management for biofloc aquaculture farmers, but it appears incremental as it applies existing IoT and ML methods to this specific domain.
The research tackled water quality prediction in biofloc aquaculture by proposing an IoT-based system that collects sensor data, analyzes it with machine learning, and uses AI for decision-making, achieving satisfactory results.
Traditional fish farming faces several challenges, including water pollution, temperature imbalance, feed, space, cost, etc. Biofloc technology in aquaculture transforms the manual into an advanced system that allows the reuse of unused feed by converting them into microbial protein. The objective of the research is to propose an IoT-based solution to aquaculture that increases efficiency and productivity. The article presented a system that collects data using sensors, analyzes them using a machine learning model, generates decisions with the help of Artificial Intelligence (AI), and sends notifications to the user. The proposed system has been implemented and tested to validate and achieve a satisfactory result.