<![CDATA[Reliable nutrient circulation is essential for small-scale hydroponic cultivation, but many Internet of Things (IoT) hydroponic systems depend on multi-parameter sensing, cloud-based decision making, or artificial-intelligence-assisted architectures that can be costly and difficult to reproduce in household and educational settings. This study designs and functionally evaluates a low-cost real-time-clock (RTC)-assisted ESP32 IoT prototype for scheduled hydroponic nutrient irrigation. The practical contribution is a reproducible entry-level automation baseline that helps household users, school laboratories, and community demonstration sites maintain predictable nutrient circulation without continuous manual checking. The system integrates an ESP32 microcontroller, DS3231 RTC, DHT11 temperature-humidity sensor, relay-driven DC nutrient pump, LCD, and Blynk monitoring interface. The main novelty is the use of battery-backed RTC scheduling as a local-first mechanism for routine nutrient-pump actuation, while the cloud dashboard is retained for supervision rather than as the sole timing dependency. This position differentiates the prototype from cloud-centered hydroponic systems whose irrigation execution may depend on network availability. The prototype was programmed to activate the nutrient pump at 07:00 and 16:00 for 10 s per event. Functional validation used four dimensions: environmental reading consistency, RTC timing consistency, pump actuation reliability, and IoT monitoring availability. Daytime DHT11 observations ranged from 29.1 to 31.2 °C and 62 to 68% RH, with mean values of 30.28 °C and 64.50% RH. The RTC showed a recorded 0-s difference from the daily reference time over five observation days within the resolution of the test. The pump executed all observed scheduled ON-OFF events, yielding 100% schedule execution success for two scheduled activations and 100% relay-pump state reliability for four observed states. The Blynk interface displayed temperature, humidity, and pump status during testing. These results demonstrate engineering feasibility for a reproducible scheduled nutrient-irrigation baseline suitable for household-scale hydroponic practice, student laboratories, and introductory IoT learning. The scope is deliberately bounded to prototype-level engineering feasibility: the study evaluates scheduling, actuation, and monitoring, but does not claim nutrient-dosing precision, flow-rate calibration, pH/EC regulation, or crop-yield improvement. Future work should include calibrated reference instruments, pH/EC and flow-rate measurement, nutrient-volume accuracy testing, network-performance analysis, power and cost benchmarking, and controlled plant-growth trials.]]>
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