Page 71 - Citiverse Use Case Taxonomy Overview - Use Case Identification Track

Transport and Mobility
Horizon

Municipal Parking Space Optimization 1

Description Example Impacts SDG Alignment
Digital twins can be used to create detailed, In Leipzig, as part of the Connected
dynamic models of municipal parking Urban Twins project, AI-driven Reduced Improved
infrastructure that monitor real-time space methods are used to analyze parking congestion quality of life
availability, usage patterns, and future space availability and usage by
demand across cities. Transport planners can combining aerial and street view
use these platforms to identify parking imagery. By integrating geo- Improved Operational
pressure points, inform policy decisions, and referenced data from mobile camera visitor/resident efficiency Target 11.2, 11.3
plan more efficient resource allocation. This is sources and aerial images, the system experience
particularly valuable for dense urban achieves a high accuracy rate of up to
environments where optimizing space 94% in detecting parking structures.
Economic
utilization directly impacts traffic congestion The results are visualized in development
and accessibility. AI can be leveraged to dashboards for city planners, enabling
automate the detection of parking occupancy data-driven decision-making to
using aerial and street imagery, predict future alleviate parking pressure, optimize
demand fluctuations, and recommend urban mobility, and support future Risk Level
dynamic management strategies to improve infrastructure planning.
mobility outcomes for residents and visitors. Public safety Low Medium High

Stakeholder acceptance Low Medium High
Key Technologies
Data privacy and security Low Medium High
Digital
Twin Metaverse AR VR MR GenAI AI IoT
Financial/operational Low Medium High

itu.int/metaverse/virtual-worlds/