Development of an Intelligent System for the Recommendation of the Most Suitable Routes for Pedestrians
This study introduces an innovative approach to urban mobility through the development of an intelligent platform for smart cities. The platform leverages social media engagement to gather citizen insights about urban challenges, particularly focusing on pedestrian mobility and safety in District 6...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2025-07-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-annals.copernicus.org/articles/X-G-2025/1027/2025/isprs-annals-X-G-2025-1027-2025.pdf |
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| _version_ | 1849721642623696896 |
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| author | M. H. Zali M. Argany M. A. Mostafavi M. A. Mostafavi |
| author_facet | M. H. Zali M. Argany M. A. Mostafavi M. A. Mostafavi |
| author_sort | M. H. Zali |
| collection | DOAJ |
| description | This study introduces an innovative approach to urban mobility through the development of an intelligent platform for smart cities. The platform leverages social media engagement to gather citizen insights about urban challenges, particularly focusing on pedestrian mobility and safety in District 6 of Tehran municipality. By encouraging users to discuss city problems, the system will collect valuable data on user preferences and experiences. The platform will utilize this crowdsourced information to provide personalized routing services that reflect the community's needs and concerns. Since the platform currently does not have active users, so a structured questionnaire was distributed to 100 participants to assess factors such as perceived safety, lighting conditions, and sidewalk width. This data was then integrated into a web-based public participation system, emphasizing the crucial role of citizen input in urban planning. Routing algorithms, including A* and Dijkstra's algorithms, were employed to identify optimized pedestrian routes based on the community feedback. Preliminary results suggest that these community-informed routes outperform conventional navigation systems, such as Google Maps, in addressing local conditions and user preferences. The platform not only enhances pedestrian experiences by prioritizing safety and accessibility but also demonstrates the potential of active citizen engagement in shaping urban environments. This approach represents a significant step towards creating more responsive and user-friendly smart cities, where citizen input directly influences urban services and planning decisions. |
| format | Article |
| id | doaj-art-a23f3e32d4d64d7f8fec816e728040d0 |
| institution | DOAJ |
| issn | 2194-9042 2194-9050 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj-art-a23f3e32d4d64d7f8fec816e728040d02025-08-20T03:11:36ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502025-07-01X-G-20251027103510.5194/isprs-annals-X-G-2025-1027-2025Development of an Intelligent System for the Recommendation of the Most Suitable Routes for PedestriansM. H. Zali0M. Argany1M. A. Mostafavi2M. A. Mostafavi3Faculty of Geography, University of Tehran, Tehran, IranFaculty of Geography, University of Tehran, Tehran, IranCenter for Interdisciplinary Research in Rehabilitation and Social Integration, Université Laval, Québec (Qc) G1V 0A6, CanadaCenter for Geospatial Data and Intelligence, Université Laval, Québec (Qc) G1V 0A6, CanadaThis study introduces an innovative approach to urban mobility through the development of an intelligent platform for smart cities. The platform leverages social media engagement to gather citizen insights about urban challenges, particularly focusing on pedestrian mobility and safety in District 6 of Tehran municipality. By encouraging users to discuss city problems, the system will collect valuable data on user preferences and experiences. The platform will utilize this crowdsourced information to provide personalized routing services that reflect the community's needs and concerns. Since the platform currently does not have active users, so a structured questionnaire was distributed to 100 participants to assess factors such as perceived safety, lighting conditions, and sidewalk width. This data was then integrated into a web-based public participation system, emphasizing the crucial role of citizen input in urban planning. Routing algorithms, including A* and Dijkstra's algorithms, were employed to identify optimized pedestrian routes based on the community feedback. Preliminary results suggest that these community-informed routes outperform conventional navigation systems, such as Google Maps, in addressing local conditions and user preferences. The platform not only enhances pedestrian experiences by prioritizing safety and accessibility but also demonstrates the potential of active citizen engagement in shaping urban environments. This approach represents a significant step towards creating more responsive and user-friendly smart cities, where citizen input directly influences urban services and planning decisions.https://isprs-annals.copernicus.org/articles/X-G-2025/1027/2025/isprs-annals-X-G-2025-1027-2025.pdf |
| spellingShingle | M. H. Zali M. Argany M. A. Mostafavi M. A. Mostafavi Development of an Intelligent System for the Recommendation of the Most Suitable Routes for Pedestrians ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | Development of an Intelligent System for the Recommendation of the Most Suitable Routes for Pedestrians |
| title_full | Development of an Intelligent System for the Recommendation of the Most Suitable Routes for Pedestrians |
| title_fullStr | Development of an Intelligent System for the Recommendation of the Most Suitable Routes for Pedestrians |
| title_full_unstemmed | Development of an Intelligent System for the Recommendation of the Most Suitable Routes for Pedestrians |
| title_short | Development of an Intelligent System for the Recommendation of the Most Suitable Routes for Pedestrians |
| title_sort | development of an intelligent system for the recommendation of the most suitable routes for pedestrians |
| url | https://isprs-annals.copernicus.org/articles/X-G-2025/1027/2025/isprs-annals-X-G-2025-1027-2025.pdf |
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