## 2 Research Methodology
### Data Extraction and Analysis
#### 2.3.1 Classification Framework
In more detail, the framework in the study consists of five layers covering most of the important characteristics of AR-based solutions, from fundamental aspects to advanced intelligent solutions, as in the following:  
* Concept & Theory
* Implementation
* Evaluation  
Figure 5: Type of papers and application field. **Layer 1: Concept & Theory**  
This layer includes Algorithm, Conceptual Framework, Evaluation Framework and Technology Adoption. Algorithm relates to technical aspects of AR/Registration/Tracking methodology. Conceptual Framework supports the development or proposal of AR solutions for proof-of-concept cases. Evaluation Framework assists in grading and selecting the right enabling elements for an AR concept or AR systems. Finally, Technology adoption is relevant to the papers that point out the current challenges, limitations and gaps which needs to be solved to facilitate a wide adoption of AR-based solutions. **Layer 2: Implementation**  
This layer consists of two sublayers, which are Software and Hardware layers. **Hardware sublayer** includes the fundamental elements of an AR system, which are a Processing Unit, an Input device, a Tracking device and a Display device. Due to the fact that the Processing Unit can be flexibly selected depending on the computing workloads of the desired tracking methods and the chosen display techniques, this paper does not consider extracting this information. Besides that, the input device is an optional element of the system because it depends on the system design and specific use case. The stimuli to trigger the AR modules could be automatically included (sensors data, camera, tracking algorithms) in the approach itself. Therefore, the paper aims to concentrate more on extracting the data regarding the Display device and Tracking methods to support for RQs. In this paper, the display devices are classified into 2 groups: In-situ display and Mobile display. An In-situ display involves a Spatial display/Projector and a Monitor/Large screen. Mobile display involves HHD and HMD. Tracking methods are categorized into 3 groups: Computer vision-based tracking (CV-based), including marker-based; markerless (NFT), model-based tracking; Sensor-based tracking and Hybrid tracking. Figure 6: The architecture layer framework of an AR system, adopted from [226]. **Software sublayer** consists of Interaction design and Content design, as well as Agent-based and Knowledge-based elements. Content design is relevant to those papers that focus more on demonstrating how the AR information is constructed and used. In this, there is no interaction between the user and the virtual information; no external database is required. Interaction design focuses more on developing and enhancing the interaction between the user and virtual objects/contents. An Agent-based system (ABS) applies an agent or multi-agent system, which originates from Artificial Intelligent (AI), enabling the autonomous, adaptive/learning, intelligent characteristics of a system. Agent-based software is a higher evolution of object-oriented software [227; 228; 229]. A Knowledge-based system (KBS) is a type of AI targeting that captures human experts' knowledge to support the autonomy of decision-making. The typical architecture of a KBS consists of a knowledge base, which contains a collection of information in each field, and an inference engine, which deduces insights from the information captured/encoded in the knowledge base. Depending on the KBS problem-solving method/approach, it can be referred as a rule-based reasoning (RBS) system that encodes expert knowledge as rules, or a case-based reasoning (CBS) system that substitutes cases for rules [230; 231; 232]. **Layer 3: Evaluation**  
This layer consists of Effectiveness and/or Usability categories that involve a user study. There is a close relationship between these two categories. The more usable a system is, the more effective it could become.