Street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science
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 hel...
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2021
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oai:doaj.org-article:babc804b9d08449bb118e735d92a509a2021-11-28T12:14:21ZStreet life and pedestrian activities in smart cities: opportunities and challenges for computational urban science10.1007/s43762-021-00024-92730-6852https://doaj.org/article/babc804b9d08449bb118e735d92a509a2021-11-01T00:00:00Zhttps://doi.org/10.1007/s43762-021-00024-9https://doaj.org/toc/2730-6852Abstract 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.Zhuangyuan FanBecky P.Y. LooSpringerarticlePedestrian ActivitiesGPSVideoWi-FiBluetoothCities. Urban geographyGF125ENComputational Urban Science, Vol 1, Iss 1, Pp 1-17 (2021) |
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Pedestrian Activities GPS Video Wi-Fi Bluetooth Cities. Urban geography GF125 |
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Pedestrian Activities GPS Video Wi-Fi Bluetooth Cities. Urban geography GF125 Zhuangyuan Fan Becky P.Y. Loo Street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science |
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. |
format |
article |
author |
Zhuangyuan Fan Becky P.Y. Loo |
author_facet |
Zhuangyuan Fan Becky P.Y. Loo |
author_sort |
Zhuangyuan Fan |
title |
Street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science |
title_short |
Street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science |
title_full |
Street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science |
title_fullStr |
Street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science |
title_full_unstemmed |
Street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science |
title_sort |
street life and pedestrian activities in smart cities: opportunities and challenges for computational urban science |
publisher |
Springer |
publishDate |
2021 |
url |
https://doaj.org/article/babc804b9d08449bb118e735d92a509a |
work_keys_str_mv |
AT zhuangyuanfan streetlifeandpedestrianactivitiesinsmartcitiesopportunitiesandchallengesforcomputationalurbanscience AT beckypyloo streetlifeandpedestrianactivitiesinsmartcitiesopportunitiesandchallengesforcomputationalurbanscience |
_version_ |
1718408163762372608 |