# Artificial Intelligence in Agriculture: Benefits, Challenges, and Trends
## 4 Artificial Intelligence in Agriculture (RQ2)
### Artificial Intelligence Technologies  
Artificial Intelligence began in the 1950s inspired by cognitive processes and neurobiology [42]. The major challenge for this originated in analyzing AI technologies when applied to agriculture and increasing food production while confronting climatic changes. There are four categories of intelligent systems: systems that think like humans, systems that act like humans, systems that think rationally, and systems that act rationally [43]. These categories refer to thinking and behavior, measuring their success in terms of fidelity to human performance or rationality. An AI system can store and manipulate data and the acquisition, representation, and manipulation of knowledge. Manipulation includes the ability to deduce (infer) new knowledge from existing knowledge. This section concerns the artificial intelligence technologies that were identified in the papers included in the SLR. The identified technologies were grouped into three main groups: cognitive science applications, robotics applications, and natural interface applications. Figure 5 shows the technologies identified in the 176 articles analyzed. IoT, big data, and cloud computing technologies served as a support for the implementation of specific AI techniques such as computer vision, robotics, machine learning, augmented reality, and virtual reality (AR & VR). Table 13 presents the main technologies identified in the 17 articles selected in the quality assessment stage and their applications. Table 14 shows the objective of this work which was to identify AI technologies and agricultural applications in selected articles. In [14], an application for irrigation, disease, and pest management stood out, [5] presented with a review of this field, and [15] developed a smart irrigation system. New technologies like agricultural digital twins were also analyzed. Agricultural digital twins are challenged to capture the interactions between living systems and their environment [22]. Figure 5: Identified AI technologies in descriptive analysis. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Technology** & **Description** & **References** \\ \hline Robotics and automation & Use of machines, computer software, and other technologies to perform tasks that substitute or replicate human actions. & [8,14,19] \\ \hline Drones and unmanned aerial vehicles (UAVs) & Aircraft without pilot on board that can be remote-controlled. & [14,25] \\ \hline Machine learning (ML) & It is a system that can autonomously modify its behavior based on its own experience with several different algorithms that can be employed for prediction accuracy and performance evaluation. & [5,21,23,24,25] \\ \hline Artificial neural networks (ANNs) & Computing systems inspired by the human brain, which can learn new things, and adapt to new and changing environments. & [15,19] \\ \hline Deep learning: convolutional neural network (CNN) & It is based on a set of algorithms related to machine learning. CNNs algorithms find patterns in images to recognize objects, classes, and categories. & [6,13,16,17,18,26] \\ \hline Genetic algorithm (GA) & Algorithms widely used in machine learning that are inspired by the processes of biological evolution to solve problems and model evolutionary systems. & [20] \\ \hline Computer vision & Computer Vision includes problems, such as object detection, motion tracking, and action recognition, using methods for acquiring, analyzing, and understanding images extracted automatically. & [6,13,16,18,19,25,26] \\ \hline Digital twins & It is a virtual representation that seeks productivity and efficiency optimizations. & [22,44] \\ \hline Internet of things (IoT) & Connects different intelligent equipment, facilitating the management of the crop. & [15,20,24,45] \\ \hline Cloud computing & On-demand availability of resources such as data storage and computing power. & [25,46,47] \\ \hline Big data & It collects, processes, and analyzes data. & [8,48] \\ \hline \hline \end{tabular}
\end{table}