National Ict Australia Limited

Yang Wang

Fang Chen

Zhidong Li

Kostia Robert

Matt Zhang

Jun Yang

Jian Zhang

The present invention generally relates to failure prediction of an infrastructure (). A failure likelihood for one or more components of an infrastructure () is determined. History data () representing prior failures of the components of the infrastructure () is applied (-) to a Bayesian nonparametric statistical model using a beta process. Then the failure likelihood of one or more components of the infrastructure from the Bayesian nonparametric statistical model is estimated (). Aspects of the invention include computer-implemented methods (), software and computer systems ().

Bayesian nonparametric method for infrastructure failure prediction

The disclosure relates to structural health monitoring (SHM). In particular determining a health condition of a structure, such as a bridge, based on vibration data measured of the bridge. Measured vibration data is calibrated (-). Features are then extracted from the calibrated data (-) and a support vector machine classifier is then applied () to the extracted features to determine () the health condition of a part of the structure. Training of the support vector machine classifier by a machine learning process () is also described.

Determining a health condition of a structure

The invention concerns a traffic surveillance system that is used to detect and track vehicles in video taken of a road from a low mounted camera. The inventors have discovered that even in heavily occluded scenes, due to traffic density or the angle of low mounted cameras capturing the images, at least one horizontal edge of the windshield is least likely to be occluded for each individual vehicle in the image. Thus, it is an advantage of the invention that the direct detection of a windshield on its own can be used to detect a vehicle in a single image. Multiple models are projected () onto an image with reference to different points in the image. The probability of each point forming part of a windshield is determined based on a correlation of the horizontal edges in the image with the horizontal edges of the windshield model referenced at that point (). This probability of neighboring points is used to possible detect a vehicle in the image (). Aspects of the invention include a method, software and traffic surveillance system.

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Eveleigh, Australia

Yang Wang