A Robust and Scalable Pipeline for the Real-time Processing and Analysis of Massive 3D Spatial Streams

Abstract

With the increase in the use of 3D scanner to sample the earth surface, there is a surge in the availability of 3D spatial data. 3D spatial data contains a wealth of information 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 due to its size, velocity and inherent noise, it is processed offline. Many applications require real-time processing and analysis of spatial stream, for-instance, forest fire management, real-time road traffic analysis, disaster engulfed areas monitoring, etc., however they suffer from slow offline processing of traditional systems. This paper presents and demonstrates a robust and scalable pipeline for the real-time processing and analysis of 3D spatial streams. An experimental evaluation is also presented to prove the effectiveness of the proposed framework.