A presentation conducted by Dr Rohan Wickramasuriya, SMART Infrastructure Facility, University of Wollongong. Presented on Tuesday the 1st of October 2013. Business Intelligence (BI) has popularly been adopted as a process that enables easy access, analysis and visualization of information through specialized set of tools for informed decision making. Two most noticeable characteristics of traditional BI is that it (a) is largely used in single-organization environments and (b) uses predominantly aspatial data. We believe that BI has applications beyond single-organization environments, but it very much requires integration of geospatial capabilities given the increasing availability of large volumes of spatial data and a growing interest to see things spatial. The SMART Infrastructure Dashboard (SID), our innovative solution that fuses BI and Geographic Information Systems (GIS), fills this significant gap. In this study, we demonstrate how SID can be used to perform spatio-temporal analysis and visualization of diverse sets of data to uncover complex interrelationships among utility usage, demographics and weather patterns at local and regional scale.

1. ENDORSING PARTNERS
SMART Infrastructure
Dashboard
The following are confirmed contributors to the business and policy dialogue in Sydney:
•
Rick Sawers (National Australia Bank)
•
Nick Greiner (Chairman (Infrastructure NSW)
Monday, 30th September 2013: Business & policy Dialogue
Tuesday 1 October to Thursday,
Dialogue
3rd
October: Academic and Policy
Presented by: Dr Rohan Wickramasuriya, SMART Infrastructure Facility,
University of Wollongong
www.isngi.org
www.isngi.org

2. SMART Infrastructure
Dashboard
Rohan Wickramasuriya

3. Outline
• Background & Problem
• Potential solution – pieces of the jigsaw
• SID – assembled jigsaw
Study area, stakeholders and data
Technical architecture and workflows
SID in action
• Conclusion and future works

4. • Many utility service providers
• Where’s the problem?
holistic view?
integrated planning?
how can I take actions?
• Difficult challenge
multiple stakeholders
dispersed datasets
diverse formats (data)
data complexity

5. • Business Intelligence (BI)
processes
people
Data
Access
Analyse
Knowledge
technology
Why BI?
ability to handle diverse & complex data
optimized data storage for fast query performance
slice & dice, drill down, roll up
captivating, easy-to-understand reports
online access

6. • Geographic Information Systems (GIS)
Why GIS?
infrastructure data largely spatial
map is a better visual

7. Public
Infrastructure
Domain
 Regional focus
 SQL driven
 No complex modelling

8. • The Illawarra region
• 5 Councils
• Infrastructure service provision
diverse providers
private & public
• Electricity distribution
1 company
 Endeavour Energy
• Water & Sewage networks
3 operators
 Sydney Water
• Solid Waste
4 operators
 REMONDIS

9. Provider
Data type
Temporal
Resolution
Spatial
Resolution
Endeavour
Elec. Consumption
Geom. network
Monthly
N/A
SA1
Sydney
Water
Water consumption
Water quality
Water demand
Discharge volumes
Power consumption
Geom. network – water
Geom. network – sewage
Quarterly
Monthly
Daily
Daily
Monthly
N/A
N/A
Postcode
Reservoirs (point)
Reservoir zone
REMONDIS
Waste volume & weight
Collection Routes
Daily
Collection Route
ABS
Demographic
Yearly
SA1
BOM
Rainfall, Temperature
Daily
Station

10. Data Sets
Data Staging & Warehousing
Electricity
Water
ETL
Staging
Database
Data
Warehouse
Geo-BI
Analytics
Analytical
Reports
Waste
Demographic
Data
Metadata Repository
Weather Data
• Software
Pentaho Data Integration
PostgreSQL/PostGIS
Yellowfin
Interactive
Dashboards
End
Users
Web
Interface

11. • What is star schema?
• Why star schema?
simple queries
fast query performance
easy to understand

12. Schema 1
Common
dimensions
Schema 2 (network)

13. • Spatial hierarchy
SA4 - SA1
• Temporal hierarchy
year - season/quarter - month - week - day

14. Seeing is believing

19. Conclusion
• Right people, data, fusion of BI & GIS (processes &
technologies) can provide the integrated vision required
for regional infrastructure governance
• SMART Infrastructure Dashboard – a proven demonstrator
that can be replicated elsewhere
• Happy to transfer knowledge & technology
• Future work
Automating spatial data handling – FME & Geotools/ArcGIS for Server
Network interdependency

20. Prof. Pascal Perez
Research Director, SMART Infrastructure Facility
pascal@uow.edu.au