An IoT-Based Real-Time Intelligent Irrigation System using Machine Learning

Irrigation is very important fact in the field of agriculture. A machine learning and Internet of Things (IoT) based irrigation system is proposed here to make irrigation process more efficient. Soil moisture and Temperature value are taken by the sensors in Raspberry Pi with the help of analog to digital converter (ADC). Serial peripheral interface (SPI) protocol is used here to do it. A machine learning model is trained with Naïve Bayes algorithm and deployed in Raspberry Pi. The machine learning model controls the irrigation system with the sensor value with almost 98.33% accuracy. A prototype project of this irrigation system is also developed with a water pump and relay to show that how accurately the system works.