|
Title:
|
AI-POWERED CROWDSOURCING FOR INCLUSIVE PUBLIC TRANSPORT ACCESSIBILITY IN PORTUGAL |
|
Author(s):
|
Kirill Tatarnikov and Firmino Oliveira da Silva |
|
ISBN:
|
978-989-8704-71-9 |
|
Editors:
|
Paula Miranda and Pedro Isaías |
|
Year:
|
2025 |
|
Edition:
|
Single |
|
Keywords:
|
AI for Accessibility, Crowdsourced Transport Data, Real-time Public Transport Monitoring, Inclusive Mobility, Machine
Learning in Urban Planning, Sustainab |
|
Type:
|
Short Paper |
|
First Page:
|
255 |
|
Last Page:
|
259 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
if you are a member please login 
|
|
Paper Abstract:
|
While prior studies have explored crowdsourcing for transport accessibility, none have integrated multimodal AI validation
(NLP + CV) with predictive modeling for real-time barrier detection in the Portuguese context. Public transport
accessibility remains a critical challenge for individuals with disabilities, particularly in Portugal, where real-time data on
infrastructure conditions and service reliability are often incomplete. This study proposes an AI-powered crowdsourcing
platform that aggregates and analyzes multimodal user reports - ranging from broken elevators to delayed buses - to
generate actionable insights for transport operators and users. By integrating natural language processing (NLP), computer
vision (CV), and predictive modeling, the system automates the validation of reports, predicts service disruptions, and
dynamically adjusts route recommendations. The research highlights how AI-driven crowdsourcing can enhance transport
sustainability by bridging data gaps, reducing operational costs, and fostering inclusive mobility. |
|
|
|
|
|
|
