A Prototype of Augmented Reality for Visualising Large Sensors’ Datasets
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 leakages sensors datasets. 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. 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 network. Necessary system architectural supports needed as well as the interface requirements for such visualizations are also discussed in this paper.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1085385Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1324
 A. Deshpande, C. Guestrin, S. Madden, J. Hellerstein, and W. Hong. Model-Driven Data Acquisition in Sensor Networks. Proceedings of Conference on Very Large Data Bases (VLDB) Conference, August, 2004.
 A. K. Dey. Providing Architectural Support for Building Context*-Aware Applications. Ph.D. thesis, Georgia Institute of Technology, 2000.
 Archana Sangole and George K. Knopf. Visualisation of randomly ordered numeric data sets using spherical self-organising feature maps. Elsevier Journal of Computer and Graphics. Vol. 27, 6, 2003, pp. 963-976.
 Betty, J. C. & Ware C. Using colour dimensions to display data dimensions, Human Factors. Vol. 30, 2, 1988, pp. 127-142.
 Borgeat Louis, Guy Godin, Francois Blais, J-Angelo Beraldin, Philippe Massicotte and Guilaume Poirier, Visualizing and analyzing large and detailed 3d datasets. Visual Information Technology Group, Institute for Information Technology, National Research Council of Canada, Ottawa, Ontario, Canada, 2005, pp.1-9.
 Bychkovskiy, V., Megerian, S., Estrin, D., & Potkonjak, M.A. Collaborative approach to in-place sensor calibration. Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN)'3, (2003).
 D. A. Keim, H. P. Kriegel. Issues in Visualizing Large Databases. Proceedings of the International Conference on Visual Database Systems (VDB-3). Lausanne, Schweiz, März, in Visual Database Systems, Chapman & Hall Ltd., 1995.
 D. A. Keim. Information visualisation and visual data mining. IEEE Transaction on Visualisation and Computer Graphics. Vol. 71, 1, 2002, pp. 100-7.
 Dam, A. S. Forsberg, D. H. Laidlaw, La Viola J. J., Jr & Simpson R. M. Immersive VR for scientific visualisation-a progress report. IEEE Computer Graphics and Applications. Vol. 20, 6, 2000, pp. 26-52.
 E. Elnahrawy and Badri Nath. Clesning and querying noisy sensors. Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications WSNA '03, 2003.
 Folorunso Olufemi A., MohdShshrizal & Sarudin KAri. An algorithm for treating uncertainties in the visualization of pipeline sensors datasets. Proceedings of the First Int'l Visual Informaatics Conf. IVIC '09, Kuala Lumpur, Malaysia, 2009, pp. 561-572.
 G. Reitmayr and D. Schmalsteig. Colloborative Augmented Reality for Outdoor Navigation and Information Browsing. Proceedings of Symp. Location Based Services and TeleCartography, pp. 31-41, 2004.
 Goose S., Güven S., Zhang S., Sudarsky S. and Navab N. PARIS: Fusing Vision-based Location Tracking with Standards-based 3D Visualization and Speech Interaction on a PDA. Proceedings of IEEE DMS 2004 International Conference on SDistributed Multimedia Systems, San Fransisco, CA, pp. 75-80.
 Gross M. Visual computing, the integration of computer graphics. Visual Perception and Imaging. Springer, Berlin, 1994.
 Han Jiawei & Micheline Kamber. Data Mining: concepts and techniques. Morgan Kaufmann Publishers, 2001.
 Hoppe, H. New quadric metric simplifying meshes with appearance attributes. Proceedings IEEE Visualization 1999. IEEE Computer Society Press, 59-66.
 Kenneth P. Fishkin, Bing Jiang, Matthai Philipose, Sumit Roy. I Sense a Disturbance in the Force: Unobtrusive Detection of Interactions with Disturbance in the Force: Unobtrusive Detection of Interactions with RFID-tagged Objects. In Ubicomp, IRS-TR-04-013 Intel Research Seattle tech memorandum. June, 2004. pp. 1-17.
 Levoy, M., Pulli, K., Curless, B., Rusinkiewicz, S., Koller, D., Pereira, L. et al., The Digital Michelangelo Project: 3D Scanning of large statutes Proceedings of ACM SIGGRAPH, Computer Graphics Proceedings, Annual Conference Series, ACM, 2000, pp. 131-144.
 MacAdam D. L. Geodesic chromaticity diagram based on variance of colour matching by 14 normal observers. Applied Optics Journal. Vol. 10, 4, 1971, pp. 1-7.
 MacAdam D. L. Visual sensitivities to colour differences in daylight. Journal of teh Optical Society of America. Vol. 32, 5, 1942, pp. 247-274.
 Mark A. Paskin, Carlos Guestrin and Jim McFadden. A robust architecture for distributed inference in sensor networks. In IPSN, 2005. pp. 1-8.
 Ronald T. Azuma. A Survey of Augmented Reality. In Presence: Teleoperators and Virtual Environments. Vol 6, 4, (August 1997). 355-385.
 S. Julier, M. Lanzagorta, Y. Baillot, L. Rosenblum, S. Feiner, T. Hollerer, and S. Sestito. Information filtering for mobile augmented reality. Proceeding of the ACM and IEEE ISAR, 2000, pp. 3-11.
 Sean White and S. Feiner. SiteLens: situated visualization techniques for urban site visits. Proceedings of the ACM CHI, Boston, MA, USA, 2009, pp. 1117-1120.
 Sean White. Interaction with the Environment: Sensor Data Visualization in Outdoor Augmented Reality-a position paper, 2009.
 Yoon, S.-E., Lindstrom, P., Pascucci, V. and Manocha, D. Cache-oblivious mesh layouts. ACM Trans. Graph, Vol. 24(3), 2005, pp. 886-893.
 Zwicker, M., R"as"anen, J., Botsch,M., Dachsbacher, C. and Pauly, M. Perspective accurate splatting, Proceedings of the Graphics Interface Conference, Canadian Human- Computer Communications Society, pp. 247-254.