A data warehouse-based decision support system for sewer infrastructure management

Taeil Park, Hyoungkwan Kim

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)


Since the inception of the Governmental Accounting Standards Board statement-34 (GASB 34) in the United States, local and state governing entities need to inspect sewer systems and collect general information about their properties. Application of the collected information in decision-making processes, however, is often problematic due to the lack of consistency and completeness of infrastructure data. In addition, most techniques involved in decision-making processes are relatively complicated and dif ficult to implement without a certain level of engineering experience and training. Consequently, the sharing and transferring of pertinent information among stakeholders is not smooth and is frequently limited. This study presents a decision support system (DSS) for the management of sewer infrastructure using data warehousing technology. The proposed decision support system automatically assigns appropriate inspection and renewal methods for each pipeline and estimates associated costs, resulting in effective and practical sewer infrastructure management from various perspectives, with corresponding levels of detail.

Original languageEnglish
Pages (from-to)37-49
Number of pages13
JournalAutomation in Construction
Publication statusPublished - 2013 Mar

Bibliographical note

Funding Information:
This work was supported by a grant ( 2010–0014365 ) from the National Research Foundation and Ministry of Education, Science, and Technology of Korea . The work was also supported in part by the Yonsei University Research Fund of 2010, Seoul, Korea . The authors also wish to thank the city of Atlanta for providing invaluable data for the successful achievement of the research.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction


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