Optimally Heterogeneous Irrigation for Precision Agriculture Using Wireless Sensor Networks

• Published in: Arabian journal for science and engineering (2011) Vol. 44; no. 4; pp. 3183 - 3195
• Main Authors: Hamouda, Yousef E. M., Phillips, Chris
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2019; Springer Nature B.V
• Subjects: Agricultural production; Computer simulation; Engineering; Extended Kalman filter; Humanities and Social Sciences; Irrigation; Irrigation water; multidisciplinary; Optimization; Remote sensors; Research Article - Computer Engineering and Computer Science; Science; Soil conditions; Soil moisture; Water consumption; Wireless sensor networks; Precision agriculture; Water irrigation; Wireless sensor networks; Random bit climbing; Extended Kalman filter
• ISSN: 2193-567X; 1319-8025; 2191-4281
• DOI: 10.1007/s13369-018-3449-y

An optimally heterogeneous irrigation (OHI) system using a wireless sensor network is developed for agricultural water irrigation, whereby a region, such as a field, is divided into a number of heterogeneous agricultural areas. An extended Kalman filter (EKF) is adopted to filter the system state including the sensed soil moisture and temperature from the associated noisy measurements. EKF is also used to predict the next system states. After that, the suboptimal irrigation water amount for each crop is proactively computed according to the crop requirements, the predicted system state and the soil conditions so that water irrigation utilization and crop yields are improved subject to the overall residual water available below a predefined level. A random bit climbing optimization method is employed to determine the suboptimal water amount for each area so that the proposed objectives are satisfied. Simulation results are compared with other traditional irrigation schemes and show that the proposed OHI approach improves water utilization, meets the heterogeneous crop requirements, copes with different soil types, prioritises crop classes and in turn enhances crop yields.