Sensor network for monitoring and fault detection in drip irrigation systems based on embedded systems

¹ Professor, Department of EEE, Aditya Engineering College, Surampalem, India
² 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
³ Department of AIMLE, GRIET, Hyderabad, Telangana, India
⁴ Department of Management, Uttaranchal Institute of Management, Uttaranchal University, Dehradun - 248007, India
⁵ Professor, Department of Mechanical Engineering, CMR College of Engineering & Technology, Hyderabad, Telangana, India

^* Corresponding author: hod_eee@aec.edu.in

Abstract

Modern agriculture relies heavily on drip irrigation systems because they effectively distribute water to plant roots, maximising both crop yield and water usage. However, maintaining agricultural output depends on making sure these systems continue to function. In order to provide real-time monitoring and control inside irrigation networks, this article leverages embedded systems technology to investigate the integration of sensor networks for monitoring and fault detection in drip irrigation. Rather than only evaluating the literature, the study attempts to propose a unique sensor network architecture and demonstrate its effectiveness through experimental evaluation. It is determined that defect detection and real-time monitoring are essential for quickly resolving problems and maximising resource use. The suggested architecture makes use of actuators, sensors, embedded systems, and communication protocols that are all thoughtfully placed to gather pertinent data, including readings of soil moisture, temperature, humidity, and pressure. Algorithms for fault detection are designed to examine sensor data and spot irregularities in the irrigation system, allowing for prompt intervention and water-use optimisation. To evaluate how well the suggested sensor network design detects and locates defects, experimental validation in actual agricultural environments is carried out. The importance of sensor networks and embedded systems in improving drip irrigation sustainability and efficiency is highlighted by this study. It highlights the need for more study to address current issues and develop sensor network capabilities especially suited for agricultural applications, and it makes suggestions on possible advantages for agriculture and water management.