# Augmented Reality in Precision Farming: Concepts and Applications
## 2 Augmented Reality in Agriculture
### AR Types and Coupled Technologies  
The previously discussed articles demonstrate the flexibility of AR within different farming contexts. While it is clear that AR is employed as means to communicate information visually, it is the integration of AR with other technologies that enables the tailored functionality for precision farming and the visual-based modality [10; 31] Therefore, the coupled technologies used in the aforementioned articles are diverse, but core commonalities are present; such as the use of on-line databases, machine learning algorithms and sensor/IoT connectivity (i.e., humidity, temperature and weather sensors). The choice of technologies can be described as dependent on the context and domain in which the application will be used, with both foundational differences and overlaps between the two application areas of crop farming and livestock management. Whilst each AR application addresses a specific need (often unique to its deployment context) resulting in aspects that might be most notable for one domain but not be relevant for the other, AR technologies do share common requirements. For example, the use of QR codes to facilitate management tasks in environments where a low region of movement in space is expected; for example for indoor dairy farming or greenhouse management [16]. However, when dealing with a more dynamic scenario, for instance livestock dispersed over a wide area or large-field crop management, synergies between the AR deployment may include the combination of GPS and computer vision algorithms, as demonstrated by [13]. Yet a notable consideration is apparent in all deployment scenarios, and that is that location is key. Whether it is a local coordinate system enabled by cameras or a geographic coordinate system using GPS sensors [15], or a hybrid approach [13], applications are only able to properly convey information through AR with an appropriate level of location awareness and suitable coupling technologies to enable the process. The type of coupled technology provides insights into the nature of the application for precision farming. In that regard, it is possible to classify the applications into specific AR types. [PERSON] et al., for example, categorize AR applications based on their functional characteristics and propose two main categories, (A) triggered and (B) view-based AR applications [32]. For this article, focus is on triggered AR applications, which as the name suggests, are AR approaches that need to be triggered by a stimuli to deliver the augmentation of reality. In contrast, view-based applications can augment content without the need of a reference in the view. Triggered applications can be of four types: (1) marker-based, (2) marker-less (location-based), (3) dynamic augmentation and (4) complex augmentation. Marker-based involves the use of a QR code pattern to initiate the AR projection. Marker-less does not require a QR code, and in some instance the user would be required to tap on screen to create the projection on their desired location. The latter two types (dynamic and complex augmentation) highlight specific types of AR marker-less applications. Figure 1 displays an overview of the reviewed works in Section 2.1 divided by AR type, based on the four classifications in [32], to provide an example of the triggered applications currently deployed within an agriculture setting. Coupled technologies are facilitators for AR. For example, without GPS to facilitate location tracking [15], it would not be possible to create a marker-less AR approach. Similarly, without the combination of more than one coupled technology, higher location accuracy might be unattainable impacting the success of [10; 12; 14; 16; 26]. As further evidence, without the combination of different technologies higher location accuracy would not be possible to achieve, which in turn would result in applications not being able to fulfil the demands of a precision farming application.