Abstract
Sustainable agricultural development is a significant solution with fast population development through the use of information and communication (ICT) in precision agriculture, which produced new methods for making cultivation further productive, proficient, well-regulated while preserving the climate. Big data (machine learning, deep learning, etc.) is amongst the vital technologies of ICT employed in precision agriculture for their huge data analytical capabilities to abstract significant information and to assist agricultural practitioners to comprehend well farming practices and take precise decisions. The main goal of this article is to acquire an awareness of the Big Data latest applications in smart agriculture and be acquainted with related social and financial challenges to be concentrated on. This article features data creation methods, accessibility of technology, accessibility of devices, software tools, and data analytic methods, and appropriate applications of big data in precision agriculture. Besides, there are still a few challenges that come across the widespread implementation of big data technology in agriculture.
Highlights
The total populace, as revealed in November 2020 is 7.8 billion according to United Nations estimates
BIG DATA CHALLENGES IN PRECISION AGRICULTURE Gathering and examining huge data produced via IoT networks and wireless sensor networks, comprising digital images and more data from unmanned aerial vehicles (UAVs), satellites, and data fusion with existing data present difficulties to the effective execution of smart farming
The ever-growing accessibility of information through developments in information and communication (ICT) appears promising for improving innovations on indispensable decision-making through enhancing precision and generalization capability of models
Summary
The total populace, as revealed in November 2020 is 7.8 billion according to United Nations estimates. Data-driven agriculture has been shown to improve crop yield, reduce cost, and ensure sustainability [5] These are not limited to agriculture but have potential solutions for several challenges faced by livestock farming . These limitations must be addressed to offer the right methodology of agricultural solutions for the generation. We provide a comprehensive analysis to provide intuitions into important research works in smart agriculture employing big data and AI with a emphasis on precision farming. We obtained a total of 77 studies that are relevant to the research goal of this review article
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