An ARDUINO-BASED IoT SMART FARM MODEL for AUTOMATED IRRIGATION and FLOOD-RESPONSIVE DRAINAGE with CLOUD MONITORING

Abstract: Climate variability, water scarcity, and flooding are persistent threats to smallholder agricultural productivity, and manual irrigation/drainage management is poorly suited to responding to these conditions in real time. This paper presents the design, implementation, and functional testing of a low-cost, Arduino Nano-based Internet of Things (IoT) smart farm model that jointly automates irrigation and flood-responsive drainage. The system integrates a thermistor, a resistive soil moisture sensor, and a water-level sensor to drive two independently actuated pumps (irrigation and drainage) through a relay/ULN2003 driver stage, with farm status relayed to a remote user via a SIM900 GPRS module to the ThingSpeak IoT platform. The control logic irrigates only when soil moisture is below a fixed threshold and ambient temperature falls within a defined range (0-35 degC), and drains only when both soil moisture and water level indicate flooding, deactivating once the water level sensor clears. Functional testing across four environmental scenarios (dry soil with conducive temperature, dry soil with non-conducive temperature, moist soil with no flood, and moist soil with flood) confirmed that the system correctly discriminates between these states and actuates the appropriate pump, with farm status correctly relayed to ThingSpeak. A full bill of engineering measurement and evaluation totalling ₦202,000 is reported. Consistent with a no-hallucination reporting standard, this paper does not claim a quantified before/after productivity improvement, since no parallel manual-baseline test bed was operated alongside the automated system; a controlled comparative field trial is identified as the necessary next step to substantiate any such claim.

Keywords: Internet of Things, smart farming, automated irrigation, flood monitoring, Arduino, ThingSpeak, precision agriculture.