Transforming Agriculture: An Insight into Decision Support Systems in Precision Farming

Ding Yi, Luo Jun, Gao Haodic, Zhang Xing, Ye Lie, Siti Sarah Maidin, Wan Hussain Wan Ishak, Walton Wider

Abstract


Precision agriculture seamlessly incorporates advanced technologies and data analysis to improve farming efficiency and sustainability through immediate resource allocation. Therefore, this study aims to synthesize research findings related to agriculture, Decision Support Systems, and precision agriculture through a systematic literature review conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The search was performed on the Scopus database, specifically focusing on publications published in English between the years 2017 and 2023. Out of 126 periodicals, a rigorous process was used to determine which publications met the specific criteria for inclusion and exclusion. As a result, only 8 relevant studies were chosen. The review emphasizes the substantial capacity of Decision Support Systems in precision agriculture, demonstrating that DSS has the capability to enhance crop yields by 15% and decrease water consumption by 20%. Through the utilization of big data, machine learning, and advanced technologies, Decision Support Systems has the potential to transform the agricultural industry by enhancing productivity, optimizing resource allocation, and enabling early identification of pests and diseases. The utilization of real-time data from Decision Support Systems empowers farmers to make well-informed choices, effectively managing production while upholding environmental sustainability. This, in turn, plays a crucial role in ensuring the economic viability of farms and enhancing global food security. However, addressing challenges like data privacy concerns, enhancing user-friendly interfaces, establishing robust data administration infrastructure, and providing adequate training and support for end-users is imperative for the successful implementation of data-driven Decision Support Systems in precision agriculture.


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Keywords


Process Innovation; Product Innovation; Agricultural Productivity; Agricultural Technology; Decision Support Systems; Food Security

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Journal of Applied Data Sciences

ISSN : 2723-6471 (Online)
Organized by : Computer Science and Systems Information Technology, King Abdulaziz University, Kingdom of Saudi Arabia.
Website : http://bright-journal.org/JADS
Email : taqwa@amikompurwokerto.ac.id (principal contact)
    support@bright-journal.org (technical issues)

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