Adapting geospatial business intelligence for regional infrastructure planning

Wickramasuriya Roban, Perez Pascal, Ma Jun, Berryman Matthew. 2013. Adapting geospatial business intelligence for regional infrastructure planning. In : Adapting to change: the multiple roles of modelling. 20th International Congress on Modelling and Simulation (MODSIM2013), Adelaide, Australia, 1-6 December 2013. Piantadosi J. (ed.), Anderssen R.S. (ed.), Boland J. (ed.). Canberra : MSSANZ, 3057-3063. ISBN 978-0-9872143-3-1 International Congress on Modelling and Simulation. 20, Adelaide, Australie, 1 Décembre 2013/6 Décembre 2013.

Résumé : Business Intelligence (BI) has traditionally been used in organizations as a strategic tool to maximize profit. When coupled with Geographic Information Systems, however, BI can be transformed into a cutting edge decision support system for planning local and regional areas, as we demonstrate in this paper. Local and regional governments often face a major challenge in terms of developing a holistic view upon disjointedly operated utility services in their jurisdictions due to data silos. This limitation has become a serious impediment to infrastructure planning and regional adaptation to changes. Geo-BI provides tools to manage data coming from multiple and disparate sources, and visualize them through online interactive userinterfaces. The SMART Infrastructure Dashboard (SID) is an innovative Geo-BI solution that includes an open-source ETL (Extract, Transform and Load) toolkit to handle various datasets, a spatially-enabled data warehouse hosted in PostgreSQL/PostGIS and proprietary BI software for creating and administering analytical reports and dashboards. SID allows planners and policy makers to analyze the interplay between the use of infrastructure services, demographics and weather parameters across multiple spatial and temporal scales. Furthermore, SID enables planners to run various what-if scenarios related to projected consumption patterns, service vulnerability of utility networks, and transportation demand management. Future research involves enabling the analysis of networks of networks through SID to understand the propagation of cascading failures and benefits in interconnected utility networks.

Classification Agris : U30 - Méthodes de recherche
U10 - Informatique, mathématiques et statistiques
E14 - Économie et politique du développement
B10 - Géographie

Auteurs et affiliations

• Wickramasuriya Roban, University of Wollongong (AUS)
• Perez Pascal, CIRAD-ES-UPR GREEN (AUS)
• Ma Jun, University of Wollongong (AUS)
• Berryman Matthew, University of Wollongong (AUS)

Source : Cirad - Agritrop (https://agritrop.cirad.fr/572412/)

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