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. 2023 Apr 5;23(7):3752.
doi: 10.3390/s23073752.

Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review

Hasyiya Karimah Adli  1 , Muhammad Akmal Remli  2 , Khairul Nizar Syazwan Wan Salihin Wong  2 , Nor Alina Ismail  1 , Alfonso González-Briones  3 , Juan Manuel Corchado  3 , Mohd Saberi Mohamad  4
Affiliations

Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review

Hasyiya Karimah Adli et al. Sensors (Basel). .

Abstract

As the most popular technologies of the 21st century, artificial intelligence (AI) and the internet of things (IoT) are the most effective paradigms that have played a vital role in transforming the agricultural industry during the pandemic. The convergence of AI and IoT has sparked a recent wave of interest in artificial intelligence of things (AIoT). An IoT system provides data flow to AI techniques for data integration and interpretation as well as for the performance of automatic image analysis and data prediction. The adoption of AIoT technology significantly transforms the traditional agriculture scenario by addressing numerous challenges, including pest management and post-harvest management issues. Although AIoT is an essential driving force for smart agriculture, there are still some barriers that must be overcome. In this paper, a systematic literature review of AIoT is presented to highlight the current progress, its applications, and its advantages. The AIoT concept, from smart devices in IoT systems to the adoption of AI techniques, is discussed. The increasing trend in article publication regarding to AIoT topics is presented based on a database search process. Lastly, the challenges to the adoption of AIoT technology in modern agriculture are also discussed.

Keywords: artificial intelligence; artificial intelligence of things; crop diseases; internet of things; post-pandemic; smart agriculture.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
From smart “Things” in IoT systems to the adoption of AI techniques.
Figure 2
Figure 2
Systematic literature review approach [32].
Figure 3
Figure 3
Number of articles published since 2017 related to this scope of study.
Figure 4
Figure 4
A framework for smart irrigation [55].
Figure 5
Figure 5
The component and functionality of VSS.
Figure 6
Figure 6
Smartphone for monitoring.
Figure 7
Figure 7
Identification of plant leaf diseases using CNN [77].
See this image and copyright information in PMC

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