ANALYSIS OF THE CURRENT STATE AND APPLICATIONS OF SPATIAL COMPUTING ACROSS VARIOUS FIELDS
DOI:
https://doi.org/10.32689/maup.it.2025.1.30Keywords:
spatial computing, augmented reality, virtual reality, mixed reality, interactive environmentsAbstract
The article explores spatial computing, an advanced technology that enables the integration of digital information and virtual content into the physical world, opening new possibilities for interaction and data analysis. The article explores the history of spatial computing development, starting from the 1960s when Ivan Sutherland introduced the concept of Sketchpad, one of the first graphical interfaces. A significant technological breakthrough occurred in the 1980s with the development of virtual reality (VR) and immersive devices, and in the 2010s, with the widespread adoption of augmented reality (AR) in mobile devices. This article defines the key concepts and terminology of spatial computing, including virtual reality, augmented reality, mixed reality, and extended reality (VR, AR, MR, XR). The study examines core technologies that enable the integration of digital content into the physical environment, such as computer vision, motion tracking systems, and spatial data visualization. Key devices that contributed to the industry’s advancement, including Microsoft HoloLens and Apple Vision Pro, are also highlighted. The application of spatial computing is analyzed separately across various fields, including education, medicine, industry, the military sector, and tourism. In education, spatial computing facilitates the creation of interactive learning environments, particularly for exploring natural sciences and technical disciplines. In medicine, this technology is used for simulating surgical procedures, treating phantom limb pain, and rehabilitating patients. In manufacturing and design, spatial computing aids in creating 3D prototypes, while in the military sector, it is utilized for training soldiers and strategic mission planning. The article also addresses the challenges associated with spatial computing, such as high technical requirements, cybersickness, limited field of view, significant cognitive load on users, and the high cost of equipment. The conclusions emphasize the necessity of further research to reduce technology costs, develop effective interaction algorithms for spatial environments, and integrate machine learning for processing large volumes of data. Spatial computing has the potential to fundamentally transform how people interact with the digital world, but overcoming technological and social barriers is essential for its full implementation.
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