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Requirements analysis for aircraft simulators is often driven by photographs and videos of the actual aircraft. An engineer may gather and organize hundreds or even thousands of source photos of various instruments and devices unique to the aircraft. Managing all of this source information and referencing it to generate software requirements can be challenging and time-consuming. This paper explores Content Based Image Retrieval (CBIR) techniques to automatically process and search those images to generate basic requirements and to facilitate reuse. An unsupervised clustering algorithm groups source images based on minimal user input. Images processed in this way can also be queried by image similarity, thereby allowing project managers to find common source material among projects. The effectiveness of these techniques is demonstrated on an example cockpit.

Aircraft maintenance is difficult and dangerous work, often involving cramped, extreme environments. Therefore, aircraft maintenance can result in damaged equipment and systems, or worse, injury to the maintainer. Furthermore, the safety of an aircraft and its passengers is largely dependent on the maintainers as well. This paper explores how Virtual Maintenance Trainers (VMTs), which are software-based simulated maintenance environments, have the potential to mitigate these risks, while reducing training time and costs. By providing a safe environment through which the maintainer can make otherwise dangerous or costly mistakes, VMTs improve the maintainer's ability to avoid these mistakes during actual maintenance. The ability to see consequences of a mistake, even in a virtual world, can be more effective than simply being informed of those consequences by an instructor.