| 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 water irrigation systems to have what we called precision irrigation or 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. This thesis shows 19
articles each of them gives the best performance algorithm for different smart
irrigation field like estimating evapotranspiration, irrigation time, amount of
water, water index to conclude the best algorithm. |
