PITA Fiscal Year 2007 Projects

Innovative Infrastructure System Assessment Technology

Framework for data management and analysis in wastewater collection systems’ inspection
Sewer maintenance is a relevant problem for municipalities and society. On the one hand, the problems faced by utility authorities for developing an efficient maintenance management include lack of adequate data, of data integration, and lack of adequate decision making support tools. The existent problems eventually lead to a reactive approach for asset management that has been advocated as a common and inadequate behavior adopted by infrastructure authorities. On the other hand, efforts for promoting better inspection techniques; as well prediction and maintenance optimization models are being developed. However, the results of new inspection techniques have been provided as separated analysis for each data output from the several sensors, rather than in an integrated way what leads to a suboptimal use of data. This has limited the impact of the new inspection data. The full potential use of all the data generated is believed to emerge from integration and fusion of the data, which would promote a positive impact on the development of deterioration and maintenance optimization model.

A major concern is the need to integrate the development of sensing technologies, and the development of data analysis methods and tools for supporting the decision making process, such as deterioration and maintenance optimization models. The proposed project aims at developing a framework for data management that links the utilities needs and the industry technological development. This will allow utilities to have a plan for the data that must be collected, along with the potential application of the data. Industry, in turn, will be able to focus in critical technologies providing data in the necessary format, granularity and periodicity. This framework will be the basis of an interactive process, in which data management will improve decision support tools, and the use of improved tools will provide better understanding of system behavior, and then trigger further data acquisition and analysis. This is a first step to achieve a more effective use of available data resources as well as for guiding future data acquisition.