A fuzzy logic based irrigation system enhanced with wireless data logging applied to the state of Qatar

Abstract

In arid regions, developing environment and crop-specific irrigation scheduling that reduces water lost via evapotranspiration is a key to a sustainable and better managed irrigation. This paper presents a practical solution based on intelligent and effective system for a field of hyper aridity in Doha–Qatar. The system consists of a feedback fuzzy logic controller that logs key field parameters through specific sensors and a Zigbee–GPRS remote monitoring and database platform. The system is easy to deploy in existing drip irrigation systems without any physical modification. For a given crop, the fuzzy logic controller acquires data from these sensors and then applies well-devised fuzzy rules to produce appropriate time and duration for irrigation. All variables are fuzzified using trapezoidal and triangular membership functions. In this fuzzification, Max–Min inference engine and Mamdani-type rule base is adopted in order to make the best decision for each situation. Typical data in summer and winter showed that the controller ensures maintaining the soil moisture above a pre-defined value with non-abrupt oscillations. The system compensates the amount of water that is lost through evapotranspiration as predicted by Penman–Monteith model and hence allows predicting future water consumption. A local station first processes and saves real-time data received from the field controller via wireless Zigbee protocol to finally transmit these data to a remote station via a GPRS link. This enhancement enables tracking system performance in real time and creating a database for analysis and improvement. It follows that the deployment of fuzzy control combined with remote data logging would foster better management of irrigation and water resources in hyper-arid lands such as Qatar.