Abstract: Numerous embodiments are disclosed for monitoring multiple utility networks and structures, such as gas pipes, water pipes, electricity networks, traffic lights, street lights, sewers, and other utilities. Local sensors detect leaks, short-circuits, and other incidents. Data from the local sensors are collected by data collection units and sent to a server over a fiber optic or wireless connection. The server optionally can superimpose depictions of the incidents over a map, blueprint, photograph, or live image using a geographic information system (GIS) or augmented reality application.

Abstract: A mobile surface scanner and associated method are disclosed. The mobile surface scanner comprises an array of laser scanners that determine surface conditions within a selected land area. The surface data is processed and imported into a geographic information system application, where the surface conditions are visualized on a map of the selected land area.

Abstract: A method and apparatus is provided which analyzes an image of an object to detect and identify defects in the object utilizing multi-dimensional wavelet neural networks. “The present invention generates a signal representing part of the object, then extracts certain features of the signal. These features are then provided to a multidimensional neural network for classification, which indicates if the features correlate with a predetermined pattern. This process of analyzing the features to detect and identify predetermined patterns results in a robust fault detection and identification system which is computationally efficient and economical because of the learning element contained therein which lessens the need for human assistance.

Abstract: A method and apparatus is provided which analyzes an image of an object to detect and identify defects in the object utilizing multi-dimensional wavelet neural networks.

Abstract: The Invention includes a method and apparatus which analyzes an image of an object to detect and identify defects in the object. The present invention utilizes a scanning technique which converts a 2-D image of the object into a 1-D image, a transformation technique which extracts relevant features from the image, and a fuzzy inferencing technique which utilizes the features generated by the transformation technique to detect and identify defects. The present invention preferably includes an off-line learning process which selects the optimum transform coefficients for a given set of defects and stores the corresponding features in a rulebase. Preferably, the wavelet transform is used as the transformation technique to provide an analysis of the image which is localized in the frequency and time domains. The present invention may also include an on-line learning process when the present invention is incorporated into a manufacturing process for real time inspection of the object being manufactured.