Open AccessA functional framework based on big data analytics for smart farming
Author(s) -
Loubna Rabhi,
Noureddine Falih,
Lekbir Afraites,
Belaid Bouikhalene
Publication year - 2021
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v24.i3.pp1772-1779
Subject(s) - big data , drone , computer science , analytics , internet of things , agriculture , variety (cybernetics) , process (computing) , data science , the internet , computer security , data mining , artificial intelligence , world wide web , geography , archaeology , biology , genetics , operating system
Big data in agriculture is defined as massive volumes of data with a wide variety of sources and types which can be captured using internet of things sensors (soil and crops sensors, drones, and meteorological stations), analyzed and used for decision-making. In the era of internet of things (IoT) tools, connected agriculture has appeared. Big data outputs can be exploited by the future connected agriculture in order to reduce cost and time production, improve yield, develop new products, offer optimization and smart decision-making. In this article, we propose a functional framework to model the decision-making process in digital and connected agriculture .