Molecular Augmented Reality for Design and Engineering (MADE): Effectiveness of AR Models on Discovery, Learning, and Education
Document Type
Conference Proceeding
Publication Date
1-1-2020
Abstract
The design and manipulation of chemical systems involves understanding the form or morphology of chemical structures. An understand of the form of chemical structure includes an understanding of the components of chemical structure, the functions of the forms and sub-components, and changes in the structure of chemical systems during interaction, maturation, or chemical processes. Viewed from a computer graphic viewpoint these chemical processes can be described and modelled as three-dimensional structures, changing shape, and interacting with other 3D structures. Furthermore, our intuition was that the visualization should be as embodied as possible and open for collaboration. In this project we seek to create a tool for collaborative, embodied visualization of biomolecules. To achieve this interaction with targeted for hand on visualizations allowing for biomolecular exploration and scientific visualization within immersive augmented reality platforms. We anticipate a tool where components can assist both in (1) biomolecule discovery and design and a subset applicable for (2) education in biomolecules. We conducted some formative research to analyze user value and requirement. For the prototype we focused on the visualization of DNA binding protein, called Zip Proteins. These proteins are transcription factors. This system is implemented across two devices that support AR capabilities: head mount display (HMD) and the mobile phone. Key development is the porting of these molecules to immersive augmented reality environment for direct interaction. Describing the advantage of the platform for this application at the broadest level, we can say that augmented reality platforms allow for full embodied interaction with the structures at any scale and contextualized by the physical background. We also discuss future plans for this platform.
Identifier
85097225757 (Scopus)
ISBN
[9783030607029]
Publication Title
Communications in Computer and Information Science
External Full Text Location
https://doi.org/10.1007/978-3-030-60703-6_22
e-ISSN
18650937
ISSN
18650929
First Page
173
Last Page
180
Volume
1294
Recommended Citation
Kum-Biocca, Hyejin Hannah; Farinas, Edgardo T.; Mistry, Nisha; and Wan, Yutong, "Molecular Augmented Reality for Design and Engineering (MADE): Effectiveness of AR Models on Discovery, Learning, and Education" (2020). Faculty Publications. 5569.
https://digitalcommons.njit.edu/fac_pubs/5569
