Smart Urban Transit Systems: A Pillar for Sustainable City Planning in Smart Cities

The accelerated urbanization of the 21st century demands innovative and sustainable approaches to managing mobility within smart cities. This research paper, "Smart Urban Transit Systems: A Pillar for Sustainable City Planning in Smart Cities," explores the pivotal role of intelligent transit systems in advancing sustainable urban development. As cities expand, challenges like traffic congestion, air pollution, and inefficiencies in public transportation intensify, necessitating transformative solutions. Smart urban transit systems harness the power of advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), and big data analytics to tackle these pressing issues. By integrating these technologies, cities can optimize traffic flow, reduce environmental impact, and enhance the efficiency and accessibility of public transportation networks. AI-driven insights enable predictive maintenance and dynamic route adjustments, while IoT-connected infrastructure facilitates seamless communication between vehicles and traffic systems. Additionally, big data analytics provides real-time insights into commuter behavior, enabling data-driven decision-making for urban planners. This paper underscores the importance of smart transit systems as a cornerstone of sustainable city planning, emphasizing their capacity to create scalable, eco-friendly solutions. By addressing key urban challenges, intelligent transit systems pave the way for smarter, more sustainable cities that prioritize mobility, environmental conservation, and quality of life.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.15710759
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
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article

Smart Urban Transit Systems: A Pillar for Sustainable City Planning in Smart Cities

Zenodo (CERN European Organization for Nuclear Research)
Smart Cities and Technologies
article

Smart Urban Transit Systems: A Pillar for Sustainable City Planning in Smart Cities

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Abstract

The accelerated urbanization of the 21st century demands innovative and sustainable approaches to managing mobility within smart cities. This research paper, "Smart Urban Transit Systems: A Pillar for Sustainable City Planning in Smart Cities," explores the pivotal role of intelligent transit systems in advancing sustainable urban development. As cities expand, challenges like traffic congestion, air pollution, and inefficiencies in public transportation intensify, necessitating transformative solutions. Smart urban transit systems harness the power of advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), and big data analytics to tackle these pressing issues. By integrating these technologies, cities can optimize traffic flow, reduce environmental impact, and enhance the efficiency and accessibility of public transportation networks. AI-driven insights enable predictive maintenance and dynamic route adjustments, while IoT-connected infrastructure facilitates seamless communication between vehicles and traffic systems. Additionally, big data analytics provides real-time insights into commuter behavior, enabling data-driven decision-making for urban planners. This paper underscores the importance of smart transit systems as a cornerstone of sustainable city planning, emphasizing their capacity to create scalable, eco-friendly solutions. By addressing key urban challenges, intelligent transit systems pave the way for smarter, more sustainable cities that prioritize mobility, environmental conservation, and quality of life.

Zenodo (CERN European Organization for Nuclear Research)
Department of Commerce (AU)
Sustainable cities and communities
Openalex Percentile: Top 45%
Smart Cities and Technologies
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Smart Urban Transit Systems: A Pillar for Sustainable City Planning in Smart Cities · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS