Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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    ARTSAM: Augmented Reality App for Tool Selection in Aircraft Maintenance
    (Springer Science and Business Media Deutschland GmbH, 2023) Satish, N.; Kumar, C.R.S.
    Aircraft Maintenance is an advanced task requiring highly skilled engineers. Facilitating the Aircraft maintenance by providing proper tools and equipment is essential in ensuring good maintenance work. Aircraft Maintenance Technicians (AMTs) require precise knowledge and customized tools to perform their duties. They are responsible for an airplane’s safety and efficiency, and rely on a few basic pieces of equipment for a wide range of jobs pertaining to airplane maintenance. Specific maintenance tasks require unique tools. And while the AMTs could probably improvise and get the job done anyway, specialized tools exist for a reason–they help get the job done correctly and improvising will lead to unnecessary labor and a compromised aircraft. For example, an incorrectly sized screwdriver or screw causes wear and tear and makes the job harder. Besides, traditional tool management requires employees to manually check in and out each tool, which is time consuming. A Tool Selector app which recognises and tags tools in real time will help AMTs in determining how it is used in a particular task. Through this app, the AMTs can be guided through animations to perform specific tasks, such as replacement of Oil Filter from an aircraft engine. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Predicting the Determinants of Augmented Reality Technologies in E-commerce Applications: A SEM and ANN Modeling
    (Springer Science and Business Media Deutschland GmbH, 2025) Anand, K.; Sheena, S.
    Augmented reality (AR) technologies are the most promising technologies for e-commerce applications. This study has used the UTAUT theory, extending with privacy risk, which may impact the user’s decision to try AR features in e-commerce apps. The paper investigated factors using a two-stage approach comprising of Structural Equation Model (SEM) and an Artificial Neural Network (ANN). The validation of the model is performed with the IBM SPSS AMOS 24 and IBM SPSS 25 software. The results revealed performance expectancy as a noteworthy determinant through the analysis. Further privacy risks involved while using AR features of online shopping apps negatively impact the influence on the choice of the users to try out the technology. The proposed model has explained the user behavioral intention with 36.7%, whereas using ANN has predicted with an accuracy of 48.9%, indicating the model has high predictive power. This study’s theoretical and practical insights will contribute to developing and refining augmented reality systems in e-commerce applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.