Open AccessCrop Recommendation on Analyzing Soil Using Machine Learning
Author(s) -
ANGÉLICA MARÍA SAETEROS HERNÁNDEZ et al.
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i6.4033
Subject(s) - agricultural engineering , agriculture , computer science , internet of things , crop , precision agriculture , productivity , crop productivity , crop cultivation , production (economics) , graphical user interface , machine learning , agronomy , world wide web , engineering , ecology , programming language , macroeconomics , economics , biology
Agriculture plays a significant role in increasing the economic development of our nation. Crop production has greatly affected due to changes in weather pattern. Emerging technologies can be used to improve productivity of the crops by converting traditional farming to precision farming. The new technologies that are used include data analysis and Internet of things (IOT). The major issue yet to be resolved is cultivating precise crop at precise time. This can be done with the help machine learning algorithms which is found to be an effective method for predicting the suitable crop. The soil parameters such as soil moisture, temperature, humidity and pH are collected from the sensors using IOT and given to Graphical User Interface (GUI). GUI gets the inputs and suggests the suitable crops. The system developed using IOT and ML greatly helps the farmers to take a valuable decision.