This study presents a work on field verification and comprehensive evaluation of a precision aquaculture framework, integrating IoT-enabled monitoring, edge-cloud computing, and federated analytics. The framework is deployed across five selected small- and medium-scale fish farms, each representing distinct environmental and operational conditions. The testing methodology includes system test level, operational acceptance tests (OAT) and user acceptance tests (UAT) to interoperability, system reliability, and usability. Additionally, real-time data collection direct from the sensors and cloud computational analysis will assess the accuracy and predictive capability of the framework in optimizing aquaculture practices. The study follows ISO/IEC/IEEE testing standards in test design and documentation, ensuring reliability and consistency in evaluation, with findings informing future refinements for improved alert, scalability, interoperability, and sustainability. © 2025 IEEE.