ABSTRACT
We all are aware of the IoT-enabled popular smart irrigation systems that help in saving resources while increasing yields for agriculture. This paper covers the aspects of creating a mobile solution for irrigation control and monitoring using Raspberry Pi, sensors etc. The sensors gather real-time data, such as; pressure, temperature humidity, various levels of water and use the functionalities on Raspberry Pi to analyze it for activating watering motor via machine learning. For data storage, remote monitoring and manual control as necessary cloud technology has been integrated. Machine learning outputs for motor activation with prediction accuracies of 95.5%, 92.2 cm, and 90% accurate are based on CNN, RNN, and ANN algorithms respectively. The study shows the promise of IoT based integrated systems toward sustainable agriculture and enhancing resource utilization.
