A Low-Cost IoT-Based Solution for Water Quality Monitoring in Aquaculture 4.0

The effectiveness of decision-making in aquaculture ponds is highly dependent on manual water parameters measurement and water quality analysis. However, the slow manual collection of these parameters presents challenges on the decision-making process and can lead to animal death, and low productivity. The Internet of Things (IoT) can play a vital role in aquaculture by allowing sensors to collect these parameters data automatically. In this context, this paper proposes and describes a low-cost IoT-based solution to support decision-making in Aquaculture 4.0 environments, by monitoring water quality and issuing alerts, both in real-time. The proposed system is integrated with an artificial intelligence model for dissolved oxygen (DO) estimation, dispensing the use of this sensor. This reduces the manufacturing cost of the IoT system, making it more accessible, specially for developing countries. Evaluation experiments were conducted to determine the precision of the collected data and showed that the system can be used in real aquaculture production environments.