Smart City Gnosys

Smart city article details

Title	A Spatial Data Pipeline For Streaming Smart City Data
ID_Doc	4864
Authors	Carthen C.; Zaremehrjardi A.; Le V.; Cardillo C.; Strachan S.; Tavakkoli A.; Dascalu S.M.; Harris F.C.
Year	2024
Published	2024 IEEE/ACIS 22nd International Conference on Software Engineering Research, Management and Applications, SERA 2024 - Proceedings
DOI	http://dx.doi.org/10.1109/SERA61261.2024.10685604
Abstract	Point cloud data in the form of LiDAR is often utilized for its spatial qualities, especially in smart city projects for tasks involving vehicles and pedestrians. However, the process in which LiDAR data is acquired can be cumbersome to setup and automate. In this paper, we introduce a streaming and an on-demand pipeline for capturing LiDAR data from Velodyne Ultra Pucks placed along northern Nevada intersections known as the Living Lab as part of a smart city project for the city of Reno. The data coming from these intersections consist of the following formats: ROS 2 bag file, PCD, LAZ, Google Draco, and PCAP. A streaming point cloud service with PCD, LAZ, and Draco was implemented to stream any of these formats, as well as to allow the user to capture the current monitored point cloud. Additionally, two on-demand web services were implemented for both the PCAP and ROS 2 bag file to enable a user to start and stop the acquisition of LiDAR data in these formats. Through our analysis, it was discovered that Draco provided the best processing time and had a wider range of options that affected the quality of the point cloud. To evaluate this pipeline, the features of existing software were compared and a discussion was provided with an analysis of the point cloud formats. © 2024 IEEE.
Author Keywords	big data; data pipeline; data streaming; data transfer; edge computing; IoT; LiDAR; MQTT; ROS; smart city

Similar Articles

Id	Similarity	Authors	Title	Published
3536	0.983	Carthen, CD; Zaremehrjardi, A; Le, VD; Cardillo, CG; Strachan, S; Tavakkoli, A; Harris, FC Jr; Dascalu, SM	A Novel Spatial Data Pipeline For Streaming Smart City Data	INTERNATIONAL JOURNAL OF SOFTWARE INNOVATION, 12, 1 (2024)
59331	0.872	Yang B.; Dong Z.; Liang F.; Mi X.	Ubiquitous Point Cloud: Theory, Model, And Applications	Ubiquitous Point Cloud: Theory, Model, and Applications (2024)
44424	0.868	Kase T.; Hasegawa K.; Watanabe K.; Miyoshi T.; Yamazaki T.	Real-Time Point Cloud Visualization For Sustainable Spatial Digital Twins	Digest of Technical Papers - IEEE International Conference on Consumer Electronics (2025)
41021	0.867	Mohd Ariff S.A.; Azri S.; Ujang U.; Choon T.L.	Organizing Smart City Data Based On 3D Point Cloud In Unstructured Database - An Overview	International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 48, 4/W3-2022 (2022)
42928	0.864	Watanabe K.; Miyoshi T.; Yamazaki T.	Preliminary Experiment On Point Cloud Collection Through 3D Mobile Crowdsensing	Digest of Technical Papers - IEEE International Conference on Consumer Electronics (2025)
15179	0.862	Badenko V.; Zotov D.; Muromtseva N.; Volkova Y.; Chernov P.	Comparison Of Software For Airborne Laser Scanning Data Processing In Smart City Applications	International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 42, 5/W2 (2019)
27797	0.861	Ortega S.; Santana J.M.; Wendel J.; Trujillo A.; Murshed S.M.	Generating 3D City Models From Open Lidar Point Clouds: Advancing Towards Smart City Applications	Lecture Notes in Intelligent Transportation and Infrastructure, Part F1384 (2021)
3535	0.861	Carthen C.D.; Zaremehrjardi A.; Le V.; Cardillo C.; Strachan S.; Tavakkoli A.; Maketitle; Harris F.C., Jr.; Dascalu S.M.	A Novel Spatial Data Pipeline For Orchestrating Apache Nifi/Minifi	International Journal of Software Innovation, 12, 1 (2023)
24454	0.86	Azuma K.; Akiyama K.; Shinkuma R.; Trovato G.; Nihei K.; Iwai T.	Estimation Of Spatial Features In 3-D-Sensor Network Using Multiple Lidars For Indoor Monitoring	IEEE Sensors Journal, 23, 7 (2023)
41134	0.859	Merkle D.; Reiterer A.	Overview Of 3D Point Cloud Annotation And Segmentation Techniques For Smart City Applications	Proceedings of SPIE - The International Society for Optical Engineering, 12269 (2022)