IoT-Enabled Smart Aquaculture Monitoring System for Sustainable Freshwater Fish Farming in Telangana: A Field-Informed Framework

Freshwater aquaculture yield depends on water quality, stocking practices, feeding management, and timely identification of environmental stress. Conventional sporadic measurements may not capture short-term fluctuations in dissolved oxygen, pH, temperature, and ammonia that affect fish health. This paper presents a field-informed Internet of Things (IoT) framework for freshwater aquaculture monitoring in Karimnagar district, Telangana, India. The system requirements were derived from a structured farm valuation reported for 15 ponds. The proposed architecture separates the sensing layer, communication layer, cloud-storage layer sensor-interface and edge-processing layer, analytics layer, and farmer-interface layer. The framework is designed to monitor dissolved oxygen, pH, temperature, total ammonia nitrogen, turbidity, and water level, while maintaining related records of stocking, disease observations, feeding, and harvest. Wi-Fi, cellular communication, or LoRa-based transmission can be selected based on the farm connectivity and deployment requirements. The methodology incorporates data-quality checks, threshold-based alerts, historical visualization, local buffering, and a authentication methodology based on reference-instrument comparison. The planned assessment methods include mean absolute error, root mean square error, packet-delivery ratio, data completeness, Bland–Altman agreement alert latency, and system availability. The involvement of this study is a regionally informed system architecture and an integrated data model linking environmental monitoring with farm-management information. This work provides a basis for prototype implementation and empirical evaluation under freshwater aquaculture conditions.