Artificial Intelligence-Enhanced PARSAT AR Software: Architecture and Implementation

This chapter offers a comprehensive exploration of the architecture and practical implementation of a mobile training system, enriched with augmented reality (AR) features and adaptive capabilities based on fuzzy logic. It commences with an overview that encapsulates the core concepts and objectives of the system, followed by a detailed exposition of its structural underpinnings. The “Overview” section provides a high-level synopsis of the mobile training system’s architecture, with a specific emphasis on its integration of AR features and its pivotal role in enhancing spatial ability training. The subsequent section, “System Architecture,” conducts an intricate examination of the system’s architecture, delineating the distinct layers involved, namely the hardware layer, software layer, and data layer. This section elucidates the interplay of components within each layer, fostering a comprehensive understanding of the system’s holistic structure. The “Hardware Layer” section delves into the physical components of the system, elucidating their roles in tracking user movements, computational processes, and facilitating user interactions in real-time. In “Software Layer,” the focus shifts to the software components, encompassing the user interface’s interactive capabilities and the 3D rendering engine’s pivotal role in creating and presenting virtual elements within the real-world context. The “Data Layer” section addresses data storage and management, encompassing marker databases for AR tracking, 3D models repositories, and interaction models defining system rules and behaviors. The chapter further illuminates the practical implementation of the system, specifically detailing the user interface’s design and its interaction with AR learning activities. Additionally, it elucidates the incorporation of a fuzzy logic controller through C# scripting, facilitating adaptive learning based on fuzzy weight parameters.