Journal of Smart and Sustainable Farming
Foundations and Challenges of Big Data Analytics for Agricultural Systems
Journal of Smart and Sustainable Farming
Received On : 15 November 2024
Revised On : 30 December 2024
Accepted On : 28 December 2024
Published On : 08 February 2025
Volume 01, 2025
Pages : 012-022
Abstract
Various methodologies have been used by agriculturists, agribusiness entities, organizations, and scholars to gather and consolidate such data. Subsequently, the collected data undergoes modification, often transitioning from a quantitative to a qualitative form. The primary objective is to obtain valuable insights from it, which could be utilized by end users and farmers to enhance their operations and enhance their likelihood of achieving success. The aforementioned factors include precise crop forecasting, precise farming techniques, intelligent agricultural practices, cultivation of superior quality seeds, and accurate meteorological and environmental predictions. To succeed in these specialized markets, it is essential to acquire proficiency in various big data analytic methodologies, such as machine learning, clustering and classification, predictive analytics, time series analytics, recommendation systems, data mining, and regression analytics. The aforementioned issues have been the subject of discourse. Furthermore, a comprehensive integration of several big data analytic approach and their application in the sector of agriculture has been accomplished. However, novel technology often come with significant challenges. The present study has investigated the challenges associated with the implementation of big data analytics within the agricultural industry, as well as strategies for further enhancing its use in this domain.
Keywords
Big Data Analytics, Information Extraction, Knowledge Management, Data Acquisition, Predictive Analytics, Intelligent Crop Recommendation System.
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Cite this Article
Dong Samuel Taye Galu, “Foundations and Challenges of Big Data Analytics for Agricultural Systems”, Journal of Smart and Sustainable Farming, pp. 012-022, 08 February 2025, doi: 10.64026/JSSF/2025002.
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© 2025 Dong Samuel Taye Galu. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.