Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3681780acmconferencesBook PagePublication PagesgisConference Proceedingsconference-collections
UrbanAI '24: Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI
ACM2024 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
SIGSPATIAL '24: The 32nd ACM International Conference on Advances in Geographic Information Systems Atlanta GA USA 29 October 2024- 1 November 2024
ISBN:
979-8-4007-1156-5
Published:
04 November 2024
Sponsors:
Recommend ACM DL
ALREADY A SUBSCRIBER?SIGN IN

Reflects downloads up to 05 Mar 2025Bibliometrics
Skip Abstract Section
Abstract

The 2nd ACM SIGSPATIAL International Workshop on Advances in Urban AI (Urban-AI 2024) brings together researchers and practitioners to discuss advancements and future directions in urban AI. Urban AI is an emerging field that combines AI, spatial computing, and urban science to address complex challenges faced by cities. The availability of extensive urban data and the growth of digitized city infrastructures have opened opportunities for data-driven machine learning approaches in urban sciences. Urban AI encompasses innovative AI techniques applied to urban problems, AI-ready urban data infrastructure, and various urban applications benefiting from AI. Its applications range from urban planning and design to traffic prediction, energy management, public safety, urban agriculture, and land use.

Skip Table Of Content Section
SESSION: Session I
research-article
A Graph Deep Learning Model for Station Ridership Prediction in Expanding Metro Networks

Due to their reliability, efficiency, and environmental friendliness, metro systems have become a crucial solution to transportation challenges associated with urbanization. Many countries have constructed or expanded their metro networks over the past ...

research-article
Smart Route: A GIS-Based Solution for Mass Transit Design and Optimization

Mass transit is a key aspect of urban planning and management. A vast network of mass transit provides various options for connectivity to individuals through extensive networks. On the other hand, a bigger network incurs a huge cost on the operator. ...

research-article
Open Access
An Advance Review of Urban-AI and Ethical Considerations

The rapid digitization of urban infrastructure and the availability of urban data have created opportunities for developing and using artificial intelligence (AI), machine learning (ML), and deep learning (DL) algorithms to address cities' difficult ...

research-article
Open Access
Generative-AI based Map Representation and Localization

In the domain of Image-Based Localization (IBL), the precise integration of street-level and satellite perspectives plays a pivotal role, particularly in dynamic urban environments. This research introduces a novel generative AI framework that ...

SESSION: Session II
research-article
Automating Bibliometric Analysis with Sentence Transformers and Retrieval-Augmented Generation (RAG): A Pilot Study in Semantic and Contextual Search for Customized Literature Characterization for High-Impact Urban Research

Bibliometric analysis is essential for understanding research trends, scope, and impact in urban science, especially in high-impact journals, such Nature Portfolios. However, traditional methods, relying on keyword searches and basic NLP techniques, ...

short-paper
Encryption Techniques for Privacy-Preserving CNN Models: Performance and Practicality in Urban AI Applications

In recent years, as urban AI applications increasingly rely on sensitive data, ensuring the privacy and security of machine learning (ML) models has become essential. The proposed research study evaluates the performance and security trade-offs of seven ...

short-paper
Open Access
SurfaceAI: Automated creation of cohesive road surface quality datasets based on open street-level imagery

This paper introduces SurfaceAI, a pipeline designed to generate comprehensive georeferenced datasets on road surface type and quality from openly available street-level imagery. The motivation stems from the significant impact of road unevenness on the ...

short-paper
MapYog - Intelligent Spatiotemporal Data Explorer

MapYog addresses the critical challenge of managing and analyzing heterogeneous, multi-granular geospatial data, a key issue in urban planning, environmental monitoring, and various geospatial applications. Existing systems often struggle to integrate ...

research-article
Open Access
Optimization of Site Selection for Free-Floating Shared Electric Vehicles Based on Deep Reinforcement Learning

As a contemporary mode of transportation for medium-to-long distances, the widespread adoption of free-floating shared electric vehicles has the potential to reduce urban carbon emissions and alleviate traffic congestion. However, this mode of ...

Contributors
  • Oak Ridge National Laboratory
  • Texas A&M University
Index terms have been assigned to the content through auto-classification.

Recommendations

Acceptance Rates

UrbanAI '24 Paper Acceptance Rate 9 of 12 submissions, 75%;
Overall Acceptance Rate 9 of 12 submissions, 75%
YearSubmittedAcceptedRate
UrbanAI '2412975%
Overall12975%