Real-Time IoT Agriculture Platform & Smart Farm Control

Abstract

Year by year the technologies are developing in most domains and fields to have lower product cost, lower process time and more efficiency. In this thesis we will show how internet of things has improved smart farming and how we merged IOT in farming and water irrigation systems to have what we called precision agriculture and smart irrigation, and we will talk about Machine Learning one of decision-making techniques in smart irrigation. ML help to have best decision in what time and how much amount of water the soil and plant need and for that we use machine learning algorithms such as KNN, SVM, naïve bayes etc. In the project, a website is linked with a Raspberry Pi system. This innovative system is designed to benefit users, particularly farmers. It allows them to control various actuators both manually and automatically. These actuators play a crucial role in managing irrigation, which is facilitated through the integration of IoT (Internet of Things) materials and protocols.