Map Matching and Real World Integrated Sensor Data Warehousing (Presentation)

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Description

The inclusion of interlinked temporal and spatial elements within integrated sensor data enables a tremendous degree of flexibility when analyzing multi-component datasets. The presentation illustrates how to warehouse, process, and analyze high-resolution integrated sensor datasets to support complex system analysis at the entity and system levels. The example cases presented utilizes in-vehicle sensor system data to assess vehicle performance, while integrating a map matching algorithm to link vehicle data to roads to demonstrate the enhanced analysis possible via interlinking data elements. Furthermore, in addition to the flexibility provided, the examples presented illustrate concepts of maintaining proprietary operational information (Fleet DNA) ... continued below

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26 p.

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Burton, E. February 1, 2014.

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Description

The inclusion of interlinked temporal and spatial elements within integrated sensor data enables a tremendous degree of flexibility when analyzing multi-component datasets. The presentation illustrates how to warehouse, process, and analyze high-resolution integrated sensor datasets to support complex system analysis at the entity and system levels. The example cases presented utilizes in-vehicle sensor system data to assess vehicle performance, while integrating a map matching algorithm to link vehicle data to roads to demonstrate the enhanced analysis possible via interlinking data elements. Furthermore, in addition to the flexibility provided, the examples presented illustrate concepts of maintaining proprietary operational information (Fleet DNA) and privacy of study participants (Transportation Secure Data Center) while producing widely distributed data products. Should real-time operational data be logged at high resolution across multiple infrastructure types, map matched to their associated infrastructure, and distributed employing a similar approach; dependencies between urban environment infrastructures components could be better understood. This understanding is especially crucial for the cities of the future where transportation will rely more on grid infrastructure to support its energy demands.

Physical Description

26 p.

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  • Presented at the 2013 Federal Committee on Statistical Methodology (FCSM) Research Conference, 4-6 November 2013, Washington, DC; Related Information: NREL (National Renewable Energy Laboratory)

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  • Report No.: NREL/PR-5400-60893
  • Grant Number: AC36-08GO28308
  • Office of Scientific & Technical Information Report Number: 1120080
  • Archival Resource Key: ark:/67531/metadc871033

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • February 1, 2014

Added to The UNT Digital Library

  • Sept. 16, 2016, 12:32 a.m.

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  • April 4, 2017, 3:33 p.m.

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Burton, E. Map Matching and Real World Integrated Sensor Data Warehousing (Presentation), article, February 1, 2014; Golden, Colorado. (digital.library.unt.edu/ark:/67531/metadc871033/: accessed November 21, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.