The Development of an Artificial Intelligence-Powered Visualization Tool for the Presentation of a Tea Cafe Startup
Numerous beverages available in Indonesia belong to the category of harmful drinks, which contributes to the country's high diabetes rate. As a result of the rising prevalence of diabetes among the population in Indonesia in recent years, primarily attributed to the growing use of harmful beverages, We.Need. Tea assistance with the rise of the tea startup. The primary objective of this startup is to establish a tea shop within the mall. In order to plan the interior design, the author requires a prototype in the form of visual support. This research aims to develop a design for a tea cafe startup employing advanced methodologies that utilize Artificial Intelligence (AI) software. The employed approach entails a solitary case study employing software for generating three-dimensional (3D) objects and artificial intelligence (AI)-driven software for rendering. The first phase of the planning process involves creating a mood board and designing a three-dimensional tea cafe layout. The final result is a 3D image that is devoid of colour, as well as one that has been filled with colour. Software powered by artificial intelligence generates this image, responding to different triggers. Images that adhere to interior design principles when selecting furniture and supporting elements will yield superior rendering outcomes and align more closely with the desired results of the company owner. In this study, the author also incorporates Sustainable Development Goals (SDGs) number 2 and 3 when examining the role of this startup.
Authors
- Andi Pramono (ORCID: https://orcid.org/0000-0002-5930-3730)
- Salsa Nabillah
- Anna Y. Q. Ho (ORCID: https://orcid.org/0000-0002-9017-3567)
- Bambang Kartono Kurniawan
- Chelytha Hariyoko
- Desy Silvia Daniswara
Institutions
- Binus University (ID)
Publication Details
- Published
- 2024-09-04
- DOI
- https://doi.org/10.1109/iciss62896.2024.10751262
- Citations
- 1
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.53