Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2000-07-19
2002-12-17
Black, Thomas (Department: 2121)
Data processing: artificial intelligence
Neural network
Learning task
Reexamination Certificate
active
06496814
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Technical Field
The present invention relates to an improved data processing system and, in particular, to a method and system for integrating spatial analysis, data mining analysis, and scheduling to efficiently schedule and monitor infrastructure maintenance.
2. Description of Related Art
The scheduling and monitoring of infrastructural repairs is an important consideration to individuals involved in the administration of state, county, city and building infrastructures. Typically, infrastructural repairs are only instituted when a failure occurs. Thus, for example, water pipe repairs are only performed when a break in a water line is encountered.
Because failures are only addressed after the failure has occurred, the negative impact on the population that makes use of these failed infrastructures is at a maximum. Furthermore, the effect of the failure, and the actual repair process, on other infrastructural components is typically not taken into account when the repair of the failed infrastructure commences.
Thus, it would be beneficial to have a method and system for scheduling and monitoring infrastructural maintenance using predictive techniques such as data mining analysis. In would further be beneficial to have a method and system for scheduling and monitoring infrastructural maintenance that uses techniques, such as spatial analysis, to identify the impact of related infrastructural components to the failed or potentially failing infrastructure.
SUMMARY OF THE INVENTION
The present invention provides a method and system for integrating spatial analysis, data mining analysis, and scheduling to efficiently schedule and monitor infrastructure maintenance. The physical locations within a region of infrastructure repairs are identified and data values for characteristics of the infrastructure repairs are compiled and stored. Data mining algorithms are used to generate input data for the formulation of a set of spatial relationships. The locations of the infrastructure repairs within the region are associated with the locations of other infrastructure elements to form a set of spatial relationships. Spatial analysis techniques are used to provide understanding of this set of spatial relationships and how they relate to the location of infrastructure elements that are likely to require maintenance.
REFERENCES:
patent: 5692107 (1997-11-01), Simoudis et al.
patent: 5745751 (1998-04-01), Nelson et al.
patent: 5970482 (1999-10-01), Pham et al.
“Preventive Maintenance using Data Mining Systems” by V. Gelmi, British Telecommunications Engineering Conf. vol. 18, pt. 2, pp. 50-54.
“Database Mining in the Northern Ireland Housing Executive” by I.C. Magill et al, IEE Colloquium on Knowledge Discovery in Databases' London, UK Feb. 2, 1995, 44pp.
Black Thomas
Carstens Yee & Cahoon LLP
Doudnikoff Gregory M.
Holmes Michael B.
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