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Computing performance indicators in detecting shipping collision

Published:28 June 2011Publication History

ABSTRACT

The need to store and analyze movement data is continuously growing as a consequence of the huge availability of data being collected through GPS receivers, mobile devices, sensors, and others technologies. This paper presents an approach for the storage and analysis of maritime transportation data in a spatial data warehouse. The aim is to identify near-miss situations, which are the contexts where collisions between ships may occur. Moreover, a key performance indicator is proposed to compute the target percentage of safe situations between ships. The proposed spatial data warehouse was modeled, implemented and loaded with the data collected by The Netherland Coastguard, and includes data of shipping movements collected by AIS (Automatic Identification System) base stations. Through the SOLAP analysis of this data set, and taking a sample safety distance of 50 meters between ships, it was possible to verify that the percentage of safe situations is of 92%, going beyond the defined target limit of 90%. The results are promising at the conceptual level and demonstrate the need for further development of key performance indicators for analyzing large movement data sets.

References

  1. del-Río-Ortega, A. and Resinas, M. 2009. Towards Modelling and Tracing Key Performance Indicators in Business Processes. In Proceedings of SISTEDES'2009.Google ScholarGoogle Scholar
  2. Eckerson, W. 2011. Performance Dashboards: Measuring, Monitoring, and Managing Your Business. 2nd. Edition. John Wiley & Sons Inc.Google ScholarGoogle Scholar
  3. Viswanathan, G. and Schneider, M. 2011. On the Requirements for User-Centric Spatial Data Warehousing and SOLAP. In 1st Int. Workshop on Spatial Information Modeling, Management and Mining (Hong Kong, 2011). Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Rivest, S., et al. 2005. SOLAP technology: Merging business intelligence with geospatial technology for interactive spatio-temporal exploration and analysis of data. In ISPRS Journal of Photogrammetry and Remote Sensing. 60, 17--33.Google ScholarGoogle ScholarCross RefCross Ref
  5. Goralski, R. I. and Gold, C. M. 2007. The development of a Dynamic GIS for Maritime Navigation Safety. In ISPRS Workshop on Updating Geo-Spatial Databases with Imagery & The 5th ISPRS Workshop on Dynamic and Multi-Dimensional GIS (China, 2007).Google ScholarGoogle Scholar
  6. Alter, S. 1992. Information Systems: a management perspective. Addison-Wesley. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Han, J. and Kamber, M. 2001. Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Shahin, A. and Mahbod, M.A. 2007. Prioritization of key performance indicators: An integration of analytical hierarchy process and goal setting. Int. Journal of Productivity and Performance Management. 56, 3, 226--240.Google ScholarGoogle ScholarCross RefCross Ref
  9. Han, J., Stefanovic, N. and Kopersky, K. 1998. Selective Materialization: An Efficient Method for Spatial Data Cube Construction. In Proceedings of PAKDD'98. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Stefanovic, N., Han, J., and Koperski, K. 2000. Object-based selective materialization for efficient implementation of spatial data cubes. IEEE Transactions on Knowledge and Data Engineering. 12, 6, 938--958. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Symmetry Corporation. 2006. Getting Started with ADAPT TM: OLAP Database Design.Google ScholarGoogle Scholar

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      • Published in

        cover image ACM Conferences
        HotPlanet '11: Proceedings of the 3rd ACM international workshop on MobiArch
        June 2011
        42 pages
        ISBN:9781450307420
        DOI:10.1145/2000172

        Copyright © 2011 ACM

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        Publication History

        • Published: 28 June 2011

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