Smart City Gnosys
Smart city article details
| Title | Smart Curb Digital Twin: Inventorying Curb Environments Using Computer Vision And Street Imagery |
|---|---|
| ID_Doc | 50728 |
| Authors | Hao H.; Wang Y. |
| Year | 2023 |
| Published | IEEE Journal of Radio Frequency Identification, 7 |
| DOI | http://dx.doi.org/10.1109/JRFID.2022.3225733 |
| Abstract | Digital Twin (DT) offers a novel framework to track, model, analyze, and anticipate complex urban processes and support data-driven decision-making. However, a premise of developing DT applications is to inventory physical urban built environment digitally, which are often lacking for small-and medium-sized cities due to limited resources. Particularly, few digital inventories have been built for urban curb environments, which have been increasingly challenged by new vehicle technologies and emerging mobility services. We propose a data-driven framework to inventory curb facilities across types and locations using computer vision (CV) and Google Street View (GSV) imagery. Specifically, we used a state-of-the-art semantic segmentation model, i.e., DeepLab V3, pre-trained on the CityScapes dataset, to detect curb facilities of interest from GSV images. We then used the Inverse Perspective Mapping (IPM) to estimate the spatial location for each detected facility and used spatial processing to aggregate and filter estimation results. We demonstrated the framework for inventorying curbs in the Innovation District in the City of Gainesville, FL. The preliminary research contributes to Smart Curb Digital Twin for more safe, accessible, and productive curb environments. © 2017 IEEE. |
| Author Keywords | computer vision; Curb environment; digital twin; smart cities; street imagery |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
23048  | 0.887 | Hao H.; Wang Y.; Du L.; Chen S. | Enabling Smart Curb Management With Spatiotemporal Deep Learning | Computers, Environment and Urban Systems, 99 (2023) |
| 19681 | 0.873 | Nokkaew P.; Leksansern A.; Jindasee P.; Kamonsantiroj S.; Srisomboon K.; Sutthisangiam N. | Development Of Digital Twin Road Infrastructure For Smart City Modeling | Lecture Notes on Data Engineering and Communications Technologies, 259 (2025) |
| 41312 | 0.865 | Shrivastav C.S.; Masola A.; Capodieci N.; Cavicchioli R. | Parking Lots Management And Visualization In The Smart City - Digital Twin Context | Proceedings - 2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023 (2023) |
| 20203 | 0.862 | Adreani L.; Bellini P.; Colombo C.; Fanfani M.; Nesi P.; Pantaleo G.; Pisanu R. | Digital Twin Framework For Smart City Solutions | DMSVIVA 2022 - Proceedings of the 28th International DMS Conference on Visualization and Visual Languages (2022) |
| 40178 | 0.856 | Blaser S.; Meyer J.; Nebiker S. | Open Urban And Forest Datasets From A High-Performance Mobile Mapping Backpack - A Contribution For Advancing The Creation Of Digital City Twins | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 43, B1-2021 (2021) |
| 55317 | 0.852 | Syed Abdul Rahman S.A.F.; Abdul Maulud K.N.; Ujang U.; Wan Mohd Jaafar W.S.; Shaharuddin S.; Ab Rahman A.A. | The Digital Landscape Of Smart Cities And Digital Twins: A Systematic Literature Review Of Digital Terrain And 3D City Models In Enhancing Decision-Making | SAGE Open, 14, 1 (2024) |