  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 strategy alongside
the inclusion criteria in order to answer to two main research questions. The
study's findings reveal patterns, relationships, networks, and trends in
applying artificial intelligence in palm tree detection over the last decade.
Despite the good results in most of the studies, the effective and efficient
management of large-scale palm plantations is still a challenge. In addition,
countries whose economies strongly related to intelligent palm services,
especially in North Africa, should give more attention to this kind of study.
The results of this research could benefit both the research community and
stakeholders.
