Smart Agriculture Framework with Automated Irrigation and Remote Monitoring

Abstract

Conventional farming practices continue to suffer from water mismanagement, high labour dependence, and inability to respond to real-time field variations. This paper presents a Smart Agriculture Framework that integrates sensor-based data acquisition, threshold-driven automated irrigation, and IoT-enabled remote monitoring to address these challenges. An Arduino microcontroller acquires readings from a soil moisture sensor (ADC pin A0) and a DHT11 temperature-humidity sensor, processes the data against configurable thresholds, and actuates a motor driver (L293D) to operate a submersible water pump when moisture falls below the critical level or temperature exceeds 40 °C. A 16×2 LCD display provides on-site parameter visualisation, while a buzzer generates audible alerts for critical conditions. The ESP32 Wi-Fi module transmits live sensor data to the Blynk IoT cloud platform via virtual pins V0 (moisture), V1 (humidity), and V2 (temperature), enabling push notifications and remote oversight through a mobile application. Proteus ISIS simulation  validated correct threshold logic and component interaction prior to hardware deployment. Laboratory trials demonstrated pump activation latency below 2.4 s, approximately 40% water conservation versus fixed-schedule irrigation, and Blynk cloud latency averaging 320 ms at 99.2% system uptime. The proposed framework delivers an affordable, scalable, and energy-conscious solution that measurably reduces manual labour while improving crop-water management efficiency.