Smart automated irrigation system with disease prediction

Abstract

Precision agriculture have gained wide popularity in recent years for its high-ranking applications such as remote environment monitoring, disease detection, insects and pests management etc. In addition, the advancement in Internet of Things (IOT) through which we can connect real world objects to obtain the information such as physical phenomenon through sensors in the field of agriculture. This paper reports on the smart automated irrigation system with disease detection. The system design includes soil moisture sensors, temperature sensors, leaf wetness sensors deployed in agriculture field, the sensed data from sensors will be compared with pre-determined threshold values of various soil and specific crops. The deployed sensors data are fed to the Arduino Uno processor which is linked to the data centre wirelessly via GSM module. The data received by the data centre is stored to perform data analysis using data mining technique such as Markov model to detect the possible disease for that condition. Finally, the analysis results and observed physical parameters are transmitted to Android smart phone and displayed on user interface. The user interface in smart phone allows remote user to control irrigation system by switching, on and off, the motor pump by the Arduino based on the commands from the Android smart phone.