Automated Asset Data Collection

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Automated Asset Data Collection

  1. 1. Automated Asset Data Collection and Integration Omar Smadi Center for Transportation Research and Education Monday, September 24, 2001 4TH National Transportation Asset Management Workshop Madison, Wisconsin 2001
  2. 2. Presentation Outline  Asset Management / Process  Why Data / Data needs  Data issues  Data collection tools  Data integration (GIS)
  3. 3. Asset Management:  A strategic approach to managing infrastructure. Its goals are:  Build, preserve, and operate facilities in a cost- effective manner  Deliver to the customers the best value for each dollar spent  Enhance the accountability and credibility of infrastructure investment decisions
  4. 4. Asset Management Process  Goals and policies  Asset inventory  Condition assessment  Decision support tools  Short and long term planning  Program implementation  Performance monitoring
  5. 5. Data?  Why do we need data?  Support decision making  Engineering (design and operation)  Economic (budgeting, planning, and programming)  Business (Legislator and public)  Levels of decision  Administrative  Management  Engineering
  6. 6. Data Needs  Inventory:  Location  Type  Age  Value  Condition:  Functional (Roughness and rutting)  Structural (Cracking and deflection)  Cost:  User  Agency  Life-cycle
  7. 7. Data Issues  Data to support decision making  Data collection:  Expensive  Time consuming  Safety implications  Data quality:  Objectivity  Consistency  Frequency
  8. 8. Data Collection Tools  Inventory:  As-built plans  Manual surveys  Video logging  Remote sensing  Condition:  Manual surveys  Automated equipment:  Video  Laser  Remote sensing
  9. 9. Data Collection Tools
  10. 10. Data Collection Tools
  11. 11. Data Collection Tools
  12. 12. Data Collection Tools
  13. 13. Data Integration  Effective data integration and data sharing results in improved information management, processing, and decision support capabilities
  14. 14. Data Integration  Advantages:  INTEGRATED DECISION MAKING  Data integrity  Timeliness  Availability/Accessibility  Completeness  Reduced duplication  Lower data acquisition cost and storage
  15. 15. Data Integration  Business process  Location referencing  Geographic information systems (GIS)  Relational databases
  16. 16. Data Integration Example Roadway Cartography Inventory Local Agencies Pavement IPMP GIS Pavement Condition Database History Pavement History & Condition
  17. 17. Data Integration Example Ride Cracking
  18. 18. Data Integration Clinton, Iowa
  19. 19. Data Integration Sioux City Woodbury County

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