Environmental quality indicators are essential tools for translating complex technical data into accessible information, facilitating communication between academia, the public, and policymakers. Among these indicators, water quality plays a crucial role in public health and environmental preservation, particularly in ecologically sensitive regions such as the Amazon. This study presents a comparative analysis of water monitoring methods in the city of Parintins, Amazonas, Brazil, contrasting an automated data collection device with embedded sensors and traditional manual sampling using pre-calibrated commercial probes. Prior to this initiative, monitoring in the region relied exclusively on manual measurements performed by local researchers, limiting both the frequency and scope of analysis. The proposed prototype was deployed on a floating platform at the Port of Parintins and operated using LoRa-based data transmission to ensure functionality in areas with limited connectivity. The monitored parameters included pH, turbidity, electrical conductivity, water temperature, and dissolved oxygen. Data collected automatically were compared with those obtained from manual probes to assess the precision, stability, and feasibility of the automated system. Our results revealed a strong correlation between both methods, with the automated approach demonstrating superior consistency and frequency of measurements. The findings support the use of the proposed system as an efficient, low-cost, and reliable alternative for continuous water quality monitoring in remote regions of the Amazon, contributing to sustainable environmental management and informed decision-making.