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Article: Street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science
Title | Street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science |
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Authors | |
Keywords | Pedestrian Activities GPS Video Wi-Fi Bluetooth |
Issue Date | 2021 |
Publisher | Springer. The Journal's web site is located at https://www.springer.com/journal/43762/ |
Citation | Computational Urban Science, 2021, v. 1, article no. 26 How to Cite? |
Abstract | Ongoing efforts among cities to reinvigorate streets have encouraged innovations in using smart data to understand pedestrian activities. Empowered by advanced algorithms and computation power, data from smartphone applications, GPS devices, video cameras, and other forms of sensors can help better understand and promote street life and pedestrian activities. Through adopting a pedestrian-oriented and place-based approach, this paper reviews the major environmental components, pedestrian behavior, and sources of smart data in advancing this field of computational urban science. Responding to the identified research gap, a case study that hybridizes different smart data to understand pedestrian jaywalking as a reflection of urban spaces that need further improvement is presented. Finally, some major research challenges and directions are also highlighted. |
Persistent Identifier | http://hdl.handle.net/10722/309892 |
ISSN | 2023 Impact Factor: 2.6 2023 SCImago Journal Rankings: 0.627 |
PubMed Central ID |
DC Field | Value | Language |
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dc.contributor.author | Fan, Z | - |
dc.contributor.author | Loo, BPY | - |
dc.date.accessioned | 2022-01-10T09:15:23Z | - |
dc.date.available | 2022-01-10T09:15:23Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Computational Urban Science, 2021, v. 1, article no. 26 | - |
dc.identifier.issn | 2730-6852 | - |
dc.identifier.uri | http://hdl.handle.net/10722/309892 | - |
dc.description.abstract | Ongoing efforts among cities to reinvigorate streets have encouraged innovations in using smart data to understand pedestrian activities. Empowered by advanced algorithms and computation power, data from smartphone applications, GPS devices, video cameras, and other forms of sensors can help better understand and promote street life and pedestrian activities. Through adopting a pedestrian-oriented and place-based approach, this paper reviews the major environmental components, pedestrian behavior, and sources of smart data in advancing this field of computational urban science. Responding to the identified research gap, a case study that hybridizes different smart data to understand pedestrian jaywalking as a reflection of urban spaces that need further improvement is presented. Finally, some major research challenges and directions are also highlighted. | - |
dc.language | eng | - |
dc.publisher | Springer. The Journal's web site is located at https://www.springer.com/journal/43762/ | - |
dc.relation.ispartof | Computational Urban Science | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Pedestrian Activities | - |
dc.subject | GPS | - |
dc.subject | Video | - |
dc.subject | Wi-Fi | - |
dc.subject | Bluetooth | - |
dc.title | Street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science | - |
dc.type | Article | - |
dc.identifier.email | Loo, BPY: bpyloo@hku.hk | - |
dc.identifier.authority | Loo, BPY=rp00608 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1007/s43762-021-00024-9 | - |
dc.identifier.pmid | 34870286 | - |
dc.identifier.pmcid | PMC8626762 | - |
dc.identifier.hkuros | 331370 | - |
dc.identifier.volume | 1 | - |
dc.identifier.spage | article no. 26 | - |
dc.identifier.epage | article no. 26 | - |
dc.publisher.place | Switzerland | - |