Visualizing Pipeline Sensors Datasets Using Augmented Reality Based Prototype

Pipeline sensors generates significant amount of multivariate datasets during normal and leak situations. Therefore we have developed a data model to effectively manage such data and enhance the computational support needed for the effective data explorations. In this paper we discuss the development of an Augmented Reality (AR)- based scientific visualization system prototype that supports identification, localisation, and 3D visualisation of oil pipeline leakages sensors datasets. A challenge of this approach is to reduce the data inefficiency powered by the disparate, repeated, inconsistent and missing attributes of most available sensors datasets. To handle this challenge, this paper aim to develop an AR-based scientific visualization interface which automatically identifies, localise and visualizes all necessary data relevant to a particularly selected region of interest (ROI) along the virtual pipeline. Necessary system architectural supports needed as well as the interface requirements for such visualizations are also discussed in this paper