Implementation of Wireless Sensor Network in Precision Irrigation and Fertilization

Abstract

This research explores the design and implementation of an Internet of Things (IoT) based system for precision irrigation and fertilization in greenhouse environments. By integrating ESP32 microcontrollers with soil moisture, temperature, and Nitrogen potassium and phosphorus (NPK) sensors, the system enables real-time monitoring and automation of irrigation and nutrient management. The system collects and transmits sensor data to a central platform via Wi-Fi, allowing users to access real-time information through a web-based interface. Automated irrigation is achieved through solenoid valves, which adjust water flow based on soil moisture levels, while fertilization suggestions are provided when nutrient deficiencies are detected in the soil. To evaluate the system's accuracy and reliability, the sensor data was compared with manual measurements obtained using conventional methods. The results showed high accuracy, with soil moisture readings differing by no more than 5% from manual measurements, and soil temperature readings within a 1% range. The NPK sensor data showed a slight discrepancy of 10-15% for nitrogen and phosphorus levels, which is acceptable for soil nutrient testing, with potassium levels showing greater accuracy (within 5%). The research demonstrates the potential of IoT systems to improve greenhouse management by enhancing resource efficiency, enabling precise environmental control, and providing actionable insights for optimal plant growth. The results are consistent with previous studies on IoT-based agricultural systems, further supporting the feasibility of this technology for modernizing greenhouse farming. The project suggests opportunities for further refinement, including advanced machine learning for improved data analysis and sensor calibration.