Leveraging Meta AI, Spatial AI, and Character AI Model for Generative Smart Cities
Files
Date
2025-01-07
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Narrator
Transcriber
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
1364
Ending Page
Alternative Title
Abstract
Cities are complex, dynamic environments, requiring huge numbers of services and systems to facilitate and better the lives of the citizens within them. Keeping up with the demands of modern life has led to the creation of Smart City Digital Twins (SCDT), which are complete and bidirectional Cyber-Physical Systems (CPS) acting as observation and control mechanisms. Current SCDTs are typically bespoke implementations, catering to the city's unique needs and footprint. Generative AI will enable the generation of broader possible visions of the city, but the current data created by SCDTs is insufficient to train generative AI. This is a common problem for AI, and synthetic data is utilised to augment the training set. This paper proposes a novel concept for the creation of synthetic data; the use of the Meta, Character, Spatial Artificial Intelligence (MCS-AI) Model to emulate and therefore build the vast amounts of synthetic data required for a City Generative AI.
Description
Keywords
Driving Innovation Intelligence in Cities: Digital Twins, Generative AI, and Cyber-Physical Systems, cyber-physical systems, generative ai, meta ai, smart city digital twins, synthetic data
Citation
Extent
10
Format
Geographic Location
Time Period
Related To
Proceedings of the 58th Hawaii International Conference on System Sciences
Related To (URI)
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.