<![CDATA[The integration of Internet of Things (IoT) technologies into water resource monitoring provides new opportunities for optimizing micro-hydro power plant (PLTMH) development. This study aimed to design, implement, and evaluate an IoT-enabled flow monitoring system using a YF-S201 flow sensor, NodeMCU microcontroller, and Blynk platform. Laboratory calibration and field deployment were conducted at the Milangi Jini Waterfall stream, Gorontalo, Indonesia, to compare the performance of the IoT system with conventional manual methods. Real-time measurements across three river segments indicated distinct flow patterns: Segment 1 exhibited unstable discharge with frequent low-flow events (1.39–3.03 L/min; average 2.13 L/min), Segment 2 maintained moderate and stable flow (3.03–4.10 L/min; average 3.65 L/min), and Segment 3 consistently achieved the highest and most stable discharge (3.46–4.75 L/min; average 3.96 L/min; total volume 4.63 m³). The IoT system outperformed conventional methods by capturing high-resolution temporal variability and enabling remote monitoring. These findings demonstrate that stable, high discharge is positively correlated with micro-hydro reliability and turbine performance, confirming Segment 3 as the most viable site for PLTMH development. Beyond technical validation, the study emphasizes the socio-economic and sustainability benefits of IoT adoption in rural electrification and energy transition strategies. The results contribute to the knowledge base by confirming IoT’s role in improving accuracy, decision-making, and sustainability in hydropower projects, while also identifying challenges related to scalability and implementation in remote contexts.]]>
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