Abstract
This paper presents extended GinisSense architecture applied for the prediction of electric power supply system behaviour. The original GinisSense architecture is a Sensor Web based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. This architecture was extended in order to process data from various IT systems present in power supply companies and sensors attached on power supply network elements. This allowed us to manage a large amount of data, both archived and real time, extract valuable information from raw data and perform rules based reasoning for the prediction of power supply system behaviour. The behaviour prediction process consists of four steps, defined according to Omnibus data fusion model. These steps lead to generation of events, where each event represents the possible future state of the power supply system indicating vulnerability of individual power supply network elements. By means of specialized Web GIS application, user is presented with the geographical area containing power supply network elements with the potential for the hazardous events. Within this paper, we demonstrate the architecture with a scenario generated in a laboratory conditions. For demonstration purposes, the necessary subset of data was transferred from the power supply company database to the laboratory conditions and the electrical values were collected from the local data warehouse during the simulation of hazardous events.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Delin, K.A., Jackson, S.P. and Some, R.R. (1999) Sensor Webs, NASA Tech Briefs, Vol. 23, pg. 80.
Simonis, I. (2008) Sensor Web Enablement Architecture 06-021r4, Open Geospatial Consortium
Veljković, N., Bogdanović-Dinić, S. and Stoimenov, L. (2010) GinisSense - Applying OGC Sensor Web Enablement, in: Proc. of the 13th AGILE Conference on GIScience, Guimaraies, Portugal.
Bogdanović-Dinić, S., Veljković, N. and Stoimenov, L. (2011) Intelligent data fusion model in GinisSense architecture, in: Proc. of the 11th SGEM conference, Albena, Bulgaria, 20-25. June, Vol. 2, pp. 613-620.
Veljković, N., Bogdanović, M., Bogdanović-Dinić, S. and Stoimenov, L. (2010) GinisSense - Visualizing Sensor Data, in: Proc. of the 10th SGEM conference, Albena, Bulgaria, 19.-25. June, pp. 1119-1126.
IrisNet, http://www.intel-iris.net/
SenseWeb, http://research.microsoft.com/en-us/projects/senseweb
GeoSwift, http://geoict.yorku.ca
Vulcano SensorWeb project, http://sensorwebs.jpl.nasa.gov/
Athanasiadis, N., Milis, M., Mitkas, P.A. and Michaelides, S.C. (2005) Abacus: A multi-agent system for meteorological radar data management and decision support, in: 6th International Symposium on Environmental Software Systems (ISESS-05), Sesimbra, Portugal
Moodley, D. and Simonis, I. (2006) A New Architecture for the Sensor Web: The SWAP Framework, in: workshop of the 5th International Semantic Web Conference ISWC
Gibbons, P.B., Karp, B., Ke, Y., Nath, S. and Seshan, S. (2003) IrisNet- An Architecture for a Worldwide Sensor Web, IEEE Pervasive Computing, Vol. 2, No. 4, pp. 22-33.
Santanche, A., Nath, S., Liu, J., Priyantha, B. and Zhao, B. (2006) Senseweb: Browsing the physical world in real time, in: IPSN’06
Liang, S.H.L., Croitoru, A. and Tao, C.V. (2005) A distributed geospatial infrastructure for Sensor Web, Computers & Geosciences, Vol. 31, No. 2, pp. 221-23.
Chien, S., Tran, D., Davies, A., Johnston, M., Doubleday, J., Castano, R., Scharenbroich, L., Rabideau, G., Cichy, B., Kedar, S., Mandl, D., Frye, S., Song, W., Kyle, P., LaHusen, R. and Cappaelare, P. (2007) Lights Out Autonomous Operation of an Earth Observing Sensor web, in: International Symposium on Reducing the Cost of Spacecraft Ground Systems and Operations (RCSGSO 2007), Moscow, Russia.
Athanasiadis, I.N. (2005) A methodology for developing agent-based systems in environmental informatics applications, Doctoral Dissertation, Electrical and Computer Engineering Dept, Aristotle University of Thessaloniki.
Marković, N., Stanimirović, A. and Stoimenov, L. (2009) Sensor Web for River Water Pollution Monitoring and Alert System, in: Proc. of the 12th AGILE International Conference on Geographic Information Science, Hannover, Germany.
Veljković, N., Bogdanović-Dinić, S., Pavlović, D. and Stoimenov, L. (2010) Applying GIS and SensorWeb for Monitoring of Fire in Protected Areas, in: Proc. of the International scientific conference on information, communication and energy systems and technologies - ICEST, Bitola, Macedonia.
Bogdanović-Dinić, S., Veljković, N. and Stoimenov, L. (2011) Sensor Web Architecture for Data Management in Power Supply Companies through Web GIS, in: Proc. of the International scientific conference on information, communication and energy systems and technologies - ICEST, Nis, Serbia.
Bedworth, M. and O’Brien, J. (2000) The Omnibus Model: A New Model of Data Fusion?. IEEE Aerospace and Electronic Systems Magazine, Vol. 15, Iss. 4.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Bogdanović, M., Veljković, N., Stoimenov, L. (2012). Spatial Sensor Web for the Prediction of Electric Power Supply System Behaviour. In: Gensel, J., Josselin, D., Vandenbroucke, D. (eds) Bridging the Geographic Information Sciences. Lecture Notes in Geoinformation and Cartography(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29063-3_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-29063-3_5
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29062-6
Online ISBN: 978-3-642-29063-3
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)