G E O S P A T I A L
Old Tricks in a New World
Julian Watts VGCPAM, BApplSc
Principal Consultant, Atkins Management Consult...
Presentation Objective: Transformation
The Future
• Utilise new international standards like ISO55000 and
PAS1192-3 to dri...
Why is quality GI needed?
•It is an essential enabler for
effective asset management...
•Better information, better
decisi...
IAM Asset Management Competency
Framework
Who needs to be trained in GI?
Geographic Information
Where GI fits in the
Management System
vv
Source: ISO Guide 83 Management Systems
Source: IAM Conference 2013 Proceedings ...
Where does AM fit in the Information
Delivery Cycle?
Source: Bsi PAS 1192-2:2013
Asset Management Information
G E O S P A T I A L
Case Study 1
Islington Asset Capture for the HAMP
Initial Demand Drivers
The need for transparent ‘Who...
How Geographic Information
Helped
• Digitised visible information from aerial photography using stereo
photogrammetric tec...
Results
• The HAMP has been developed from a user’s perspective
with a user hierarchy for investment
• Behavioural, social...
What the Future Holds
• Image based mobile 3D mapping
• High-resolution panoramic images
• 3D data for every pixel
• Utili...
G E O S P A T I A L
Case Study 2
DLR Rail Condition Survey
Initial Demand Drivers
The need to manage budget and
possession...
How Geographic Information
Helped
• Visually showed measurements on a map – snapped to the track
• Additional functionalit...
• Able to correlate high wear with speed, gradient and rolling stock
hunting
• Provided a baseline for subsequent inspecti...
What the Future Holds
• Link the value of information with economic gains
• Model degradation vs. cost of replacement and ...
G E O S P A T I A L
Case Study 3
Local Authority Asset Ownership Framework
Initial Demand Drivers
The need for accountable...
How Geographic Information
Helped
• Enabled visual confirmation and verification of asset boundaries
• Created a platform ...
Results
• Clear framework for understanding most appropriate party to
manage each asset
• Identified a platform for how to...
What the Future Holds
• A wider team involved with more cross organisation
collaboration
• Clear line of sight of benefits...
How I see the Future of Geospatial &
Location Analytics for Asset Management
• The Board room will recognise the value tha...
Julian Watts - AGI Asset Management SIG (Sep 2013)
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Julian Watts - AGI Asset Management SIG (Sep 2013)

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Julian Watts - AGI Asset Management SIG (Sep 2013)

  1. 1. G E O S P A T I A L Old Tricks in a New World Julian Watts VGCPAM, BApplSc Principal Consultant, Atkins Management Consultants Committee Member AGI AM SIG, Council Member IAM, Fellow RGS 6th September 2013 AGI Asset Management Special Interest Group The Future of Geospatial and Location Analytics for Asset Management
  2. 2. Presentation Objective: Transformation The Future • Utilise new international standards like ISO55000 and PAS1192-3 to drive corporate support • Use alignment to maximise value from geographic information to deliver asset management and organisational objectives • Exploit access to Big Data The Past • GI was an add-on to projects with no ring-fenced budget • Not able to sell the benefits beyond a visual front end to a database • Leads to proof of concepts that aren’t sustainable • Usually preconceived ideas about a solution
  3. 3. Why is quality GI needed? •It is an essential enabler for effective asset management... •Better information, better decisions, better performance... GFMAM Asset Management Landscape Geographic Information
  4. 4. IAM Asset Management Competency Framework Who needs to be trained in GI? Geographic Information
  5. 5. Where GI fits in the Management System vv Source: ISO Guide 83 Management Systems Source: IAM Conference 2013 Proceedings - View from FDIS for ISO55001 Geographic Information
  6. 6. Where does AM fit in the Information Delivery Cycle? Source: Bsi PAS 1192-2:2013 Asset Management Information
  7. 7. G E O S P A T I A L Case Study 1 Islington Asset Capture for the HAMP Initial Demand Drivers The need for transparent ‘Whole of Government Accounts’ Create an asset register for 217 kilometres of highway for: – Signs, posts, road markings, bus cages, carriageway and footway – Condition, dimensions, diagram number, material, colour
  8. 8. How Geographic Information Helped • Digitised visible information from aerial photography using stereo photogrammetric techniques • Data capture and editing tools were created to work within ArcGIS that facilitated digitisation of assets and some attributes • Surveyors worked with tablet PCs loaded with ArcView software • New assets could be added from a pre-defined list with workflow to force front-end attribution Digitised Assets Field Application User Interface
  9. 9. Results • The HAMP has been developed from a user’s perspective with a user hierarchy for investment • Behavioural, social, economic and activity data can be overlaid enabling rich information • Data maintenance requirements were identified to cover 10% per year plus new developments How did it score?Almost there!!
  10. 10. What the Future Holds • Image based mobile 3D mapping • High-resolution panoramic images • 3D data for every pixel • Utilise social media imagery for historic condition • Utilise access to increasing remotely sensed data
  11. 11. G E O S P A T I A L Case Study 2 DLR Rail Condition Survey Initial Demand Drivers The need to manage budget and possessions The need to understand track degradation Visualise the track measurements for: – Head Wear – Inner Side Wear – Outer Side Wear
  12. 12. How Geographic Information Helped • Visually showed measurements on a map – snapped to the track • Additional functionality using a smartphone accelerometer and GPS to measure speed profiles, longitudinal and lateral acceleration and gradient Head Wear Side Wear Altitude Speed lateral Accel
  13. 13. • Able to correlate high wear with speed, gradient and rolling stock hunting • Provided a baseline for subsequent inspections Track Head and Side Wear Speed lateral Accel Results
  14. 14. What the Future Holds • Link the value of information with economic gains • Model degradation vs. cost of replacement and journey time • Agreed data capture specifications and timeframes • A ‘network of things’ where assets return real time monitoring info • Intelligent infrastructure & real time remote condition monitoring • Maximise use of crowd sourcing from smartphones and social media How did it score?It could do better!!
  15. 15. G E O S P A T I A L Case Study 3 Local Authority Asset Ownership Framework Initial Demand Drivers The need for accountable cost centres The need for contract packaging Needed to understand optimum teams for: – Ownership – Operations – Contractor
  16. 16. How Geographic Information Helped • Enabled visual confirmation and verification of asset boundaries • Created a platform to set database level rules for asset stewardship
  17. 17. Results • Clear framework for understanding most appropriate party to manage each asset • Identified a platform for how to identify the steward when new assets enter the EAMS and how to maintain data relationships Stewardship Register Process for Identification
  18. 18. What the Future Holds • A wider team involved with more cross organisation collaboration • Clear line of sight of benefits for understanding stewardship • Dynamic analysis of the best party to undertake maintenance vs. renewals How did it score?It could do better!!
  19. 19. How I see the Future of Geospatial & Location Analytics for Asset Management • The Board room will recognise the value that GI brings to meeting organisational objectives leading to: »Better »Faster »Supported »Structured »More

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