Leveraging Artificial Intelligence Techniques for Smart Palm Tree Detection: A Decade Systematic Review
Yosra Hajjaji, Wadii Boulila, Imed Riadh Farah

TL;DR
This systematic review analyzes a decade of research on AI-based palm tree detection, highlighting progress, challenges, and future directions for improving large-scale plantation management and supporting economic development in key regions.
Contribution
It provides a comprehensive synthesis of AI techniques used for palm tree detection from 2011 to 2021, identifying trends, challenges, and gaps in the field.
Findings
AI has shown promising results in palm detection.
Large-scale management remains a challenge.
North African countries need more focus on this research area.
Abstract
Over the past few years, total financial investment in the agricultural sector has increased substantially. Palm tree is important for many countries' economies, particularly in northern Africa and the Middle East. Monitoring in terms of detection and counting palm trees provides useful information for various stakeholders; it helps in yield estimation and examination to ensure better crop quality and prevent pests, diseases, better irrigation, and other potential threats. Despite their importance, this information is still challenging to obtain. This study systematically reviews research articles between 2011 and 2021 on artificial intelligence (AI) technology for smart palm tree detection. A systematic review (SR) was performed using the PRISMA approach based on a four-stage selection process. Twenty-two articles were included for the synthesis activity reached from the search…
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Taxonomy
TopicsDate Palm Research Studies · Oil Palm Production and Sustainability
MethodsPathways Language Model
