Revolutionization of augmented reality in tourism via deep learning - Yasmin Chuupa Essa; Saumya Chaturvedi; Shiraz Khurana (Institute of Advanced Engineering and Science, 2024)
Tourism has become an integral part of social and economic development across the globe. It does not only serve as a recreational activity but also as a source of revenue for the nation. The paper systematically explores the potential enhancements in the tourist experience through cutting-edge technology. Employing deep learning methods, the study specifically concentrates on refining augmented reality encounters for visitors. The proposed approach utilizes deep learning algorithms to optimize and tailor tourists’ augmented reality experiences, addressing current sectoral challenges like customization and engagement shortcomings. The methodology’s selection is predicated on it is capability to elevate user experience, accurately identify objects, offer visual guided tours, integrate historical context, and ultimately propel augmented reality adoption in tourism. Notably, the investigation culminates in a noteworthy average accuracy of 99% when incorporating deep learning to enhance augmented reality in tourism.