Smart City Gnosys
Smart city article details
| Title | 5G-Cage: A Context And Situational Awareness System For City Public Safety With Video Processing At A Virtualized Ecosystem |
|---|---|
| ID_Doc | 286 |
| Authors | Lopez-De-Teruel P.E.; Gil Perez M.; Garcia Clemente F.J.; Ruiz Garcia A.; Martinez Perez G. |
| Year | 2019 |
| Published | Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019 |
| DOI | http://dx.doi.org/10.1109/ICCVW.2019.00336 |
| Abstract | In this article we present 5G-CAGE, an ongoing project aimed to deploy a city safety solution that enables monitoring and analytics of video streams collected from distributed sources of a Smart City. Unlike current proposals based on inflexible architectures or limited networks, 5G-CAGE leverages 5G's high throughput and low latency, as well as its enhanced dynamism and adaptability with advanced virtualization-based technologies. In this context, 5G-CAGE defines a virtualization-enabled solution called City Object Detection (CODet), which allows recognizing interest objects in safety related situations, such as vehicles (e.g. license plates or brands), obstacles in emergency settings, or human faces recognition, to name a few. It can process multiple streams collected from fixed and moving cameras used as a distributed visual sensing system, adequately combining image processing and computer vision algorithms in a virtualized ecosystem. This paper presents initial tests in the specific task of locating and recognizing vehicle license plates, where the CODet virtualized solution has been successfully integrated and tested in the 5GINFIRE platform, an EU-funded project which provides a playground wherein new components, architectures, and APIs may be tried and proposed before being ported to 5G networks. © 2019 IEEE. |
| Author Keywords | 5G networks; Distributed sensing; Moving cameras; Smart cities; Virtualization |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
8821  | 0.878 | Silva A.P.; Bunyakitanon M.; Vassallo R.F.; Nejabati R.; Simeonidou D. | An Open 5G Nfv Platform For Smart City Applications Using Network Softwarization | 2019 IEEE Wireless Communications and Networking Conference Workshop, WCNCW 2019 (2019) |
| 24043 | 0.857 | Horvath K.; Kimovski D.; Kitanov S.; Prodan R. | Enhancing Traffic Safety With Ai And 6G: Latency Requirements And Real-Time Threat Detection | 2025 10th International Conference on Information and Network Technologies, ICINT 2025 (2025) |
| 61398 | 0.855 | Rossini E.; Pietri M.; Picone M.; Grazia C.A.; Mamei M. | Vulnerable Road Users Accident Prevention Via Smart City Data Fusion: Experimental Evaluation Of A 5G Mec Architecture | Proceedings - 2024 22nd International Symposium on Network Computing and Applications, NCA 2024 (2024) |
| 14245 | 0.854 | Er N.I.; Singh K.D.; Bonnin J.-M. | Cityview: A Vehicle Based Image And Data Collection For Smart Cities | International Conference on Wireless and Mobile Computing, Networking and Communications, 2019-October (2019) |
| 15067 | 0.851 | Hasan M.; Alavee K.A.; Bin Bashar S.Z.; Rahman M.T.; Hossain M.I.; Rabiul Alam M.G. | Comparative Study Of Object Detection Models For Safety In Autonomous Vehicles, Homes, And Roads Using Iot Devices | Proceedings of the 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023 (2023) |