Smart City Gnosys

Smart city article details

Title	A Distance-Window Based Real-Time Processing Of Spatial Data Streams
ID_Doc	1502
Authors	Shaikh S.; Matono A.; Kim K.-S.
Year	2019
Published	Proceedings - 2019 IEEE 5th International Conference on Multimedia Big Data, BigMM 2019
DOI	http://dx.doi.org/10.1109/BigMM.2019.00-33
Abstract	Real-time and continuous processing of citywide spatial data is an essential requirement of smart cities to guarantee the delivery of basic life necessities to its residents and to maintain law and order in it. With the availability of low cost 3D scanners recently, citywide 3D spatial data can be obtained easily. 3D spatial data contains a wealth of information including images, point-cloud, GPS/IMU measurements, etc., and can be of potential use if integrated, processed and analyzed in real-time. The 3D spatial data is generated as continuous data stream, however traditionally it is processed offline. Many smart city applications require real-time integration, processing, and analysis of spatial stream, for-instance, forest fire management, real-time road traffic analysis, disaster engulfed areas monitoring, people flow analysis, etc., however they suffer from slow offline processing of traditional systems. To make the most of this wealthy data resource, it must be processed and analyzed in real-time. This paper presents a framework for the continuous and real-time processing and analysis of 3D spatial streams. Furthermore, we propose a distance-based window for the continuous queries over 3D spatial streams. An experimental evaluation is also presented to prove the effectiveness of the proposed framework and the distance-based window. © 2019 IEEE.
Author Keywords	3D spatial data; Continuous query; Data stream; Distance-based window; Point-cloud data; Real-time processing

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