Soil Moisture and Rain Prediction Based Irrigation Controller for the Strawberry Farm of La Trinidad, Benguet

Strawberry farming is an important and integral part of the economy of La Trinidad, Benguet. The Strawberry Farm had been a top tourist destination not only for its known "strawberry picking" but also for the nice attraction of the strawberry plants. Needless to say, higher production and better quality of strawberries are of primary concern of the municipality. Strawberries are sensitive to the water content of the soil; hence, soil moisture monitoring is necessary to achieve timely watering. Automatic irrigations use sensors to measure soil moisture. The sensor sends the signal to activate the water valve based on soil moisture content. However, rain may occur right after watering takes place, thus, possible over-moisture of the soil may happen. Prediction of occurrence of rainfall may be necessary in order to postpone the watering of plants which in turn can further reduce the consumption of water. More importantly, available water can be reserved for other purposes. This study uses weather data in predicting rainfall to augment the soil moisture data. This will further enhance the watering schedule of the strawberry farm. ANN was used to relate the various weather parameters in the prediction of occurrence of rainfall. Training accuracy is 95% whereas when validated using the testing data, the accuracy of the model is 80%. The system promotes efficient use of water without compromising strawberry quality and production.