IoT-based Soil Moisture Monitoring System for Efficient Water Usage in Agriculture
Keywords:
Automated irrigation, Crop recommendation, IoT in farming, Precision agriculture, Smart irrigation, Soil moistureAbstract
Problem: Agriculture accounts for ~70% of global freshwater withdrawal, yet traditional gravity-fed irrigation wastes up to 40% of applied water.
Solution: We present a low-cost IoT platform that couples capacitive soil-moisture sensing (±2% accuracy) with simulated soil-PH analysis to (i) trigger irrigation automatically and (ii) recommend compatible crops. A laboratory prototype was physically implemented on a 1 m² soil bed and digitally replicated in wokwi to stress-test firmware logic.
Methods: An ESP32 aggregates moisture and pH data at 30 s intervals, publishes to ThingSpeak, and closes a relay when θv<30%. A lookup controller maps pH readings to suitable crops. Performance was benchmarked against manual irrigation for seven days.
Outcome: The smart system reduced irrigation runtime by 34.8%, saving 1.8 L day⁻¹ compared with the baseline, while maintaining leaf-water potential within ±3% of control. Data latency averaged <600 ms, and MQTT packet loss was 0% on a 2.4 GHz link.
