Intelligent drip irrigation: Leveraging embedded systems and sensor networks for real-time monitoring and fault diagnosis

¹ Department of Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore, 641021, India
² Department of Mechanical Engineering, Karpagam Institute of Technology, Coimbatore, 641105, India
³ Department of Structurals Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq; Department of Structurals Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq; Department of Structurals Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq
⁴ Department of AIMLE, GRIET, Hyderabad, Telangana, India
⁵ Professor, Department of Mechanical Engineering, CMR College of Engineering & Technology, Hyderabad, Telangana, India

^* Corresponding author: kalidas.natarajan@kahedu.edu.in

Abstract

Recent advancements in wireless sensor networks (WSNs) and precision agriculture have captured significant interest in both research and industry. Integrating WSNs into agriculture offers numerous benefits, including enhanced crop quality, improved production efficiency, resource conservation (water and energy), and optimized crop management practices (such as irrigation and fertilization). Irrigation, a crucial factor for agricultural success, is often hampered by current systems’ inefficiencies and rising production demands. Water scarcity, drought, and limited water resource waste further complicate conventional irrigation. To address these issues, we propose an intelligent irrigation system prototype that combines WSN technology with drip irrigation. This system utilizes WSNs and ZigBee wireless communication to create an automated and intelligent irrigation solution that conserves water, enhances irrigation system performance, and improves efficiency. Sensor data collected from strategically placed sensors near plant roots (including temperature and soil moisture) is used to control irrigation. The system analyses this data against predefined thresholds for each parameter and activates or deactivates irrigation accordingly. This approach aims to achieve significant water, time, and energy savings.