Abstract: An apparatus for analyzing a payload being transported in a load carrying container of a vehicle is disclosed. The apparatus includes a camera disposed to successively capture images of vehicles traversing a field of view of the camera. The apparatus also includes at least one processor in communication with the camera, the at least one processor being operably configured to select at least one image from the successively captured images in response to a likelihood of a vehicle and load carrying container being within the field of view in the at least one image, and image data associated with the least one image meeting a suitability criterion for further processing. The further processing includes causing the at least one processor to process the selected image to identify a payload region of interest within the image and to generate a payload analysis within the identified payload region of interest based the image data associated with the least one image.

Abstract: A computer processor implemented method and system for monitoring a condition associated with operating heavy equipment is disclosed. The method involves receiving a plurality of images at an interface of an embedded processor disposed on the heavy equipment, the images providing a view of at least an operating implement of the heavy equipment. The method also involves processing each of the plurality of images using a first neural network implemented on the embedded processor, the first neural network having been previously trained to identify regions of interest within the image. Each region of interest has an associated designation as at least one of a critical region suitable for extraction of critical operating condition information required for operation of the heavy equipment, and a non-critical region suitable for extraction of non-critical operating condition information associated with the operation of the heavy equipment.

Abstract: A method and apparatus for processing an image of fragmented material to identify fragmented material portions within the image is disclosed. The method involves receiving pixel data associated with an input plurality of pixels representing the image of the fragmented material. The method also involves processing the pixel data using a convolutional neural network, the convolutional neural network having a plurality of layers and producing a pixel classification output indicating whether pixels in the input plurality of pixels are located at one of an edge of a fragmented material portion, inwardly from the edge, and at interstices between fragmented material portions. The convolutional neural network includes at least one convolution layer configured to produce a convolution of the input plurality of pixels, the convolutional neural network having been previously trained using a plurality of training images including previously identified fragmented material portions.

Abstract: A method and apparatus for locating and/or determining the condition of a wear part in an image of an operating implement associated with heavy equipment is disclosed. The method involves capturing at least one image of the operating implement during operation of the heavy equipment, the image including a plurality of pixels each having an intensity value. The method also involves selecting successive pixel subsets within the plurality of pixels, and processing each pixel subset to determine whether pixel intensity values in the pixel subset meet a matching criterion indicating a likelihood that the pixel subset corresponds to the wear part. The matching criterion is based on processing a labeled set of training images during a training exercise prior to capturing the at least one image of the operating implement.

Abstract: A method and apparatus for processing an image of fragmented material to identify fragmented material portions within the image is disclosed. The method involves receiving pixel data associated with an input plurality of pixels representing the image of the fragmented material. The method also involves processing the pixel data using a convolutional neural network, the convolutional neural network having a plurality of layers and producing a pixel classification output indicating whether pixels in the input plurality of pixels are located at one of an edge of a fragmented material portion, inwardly from the edge, and at interstices between fragmented material portions. The convolutional neural network includes at least one convolution layer configured to produce a convolution of the input plurality of pixels, the convolutional neural network having been previously trained using a plurality of training images including previously identified fragmented material portions.

Abstract: A method and apparatus for locating and/or determining the condition of a wear part in an image of an operating implement associated with heavy equipment is disclosed. The method involves capturing at least one image of the operating implement during operation of the heavy equipment, the image including a plurality of pixels each having an intensity value. The method also involves selecting successive pixel subsets within the plurality of pixels, and processing each pixel subset to determine whether pixel intensity values in the pixel subset meet a matching criterion indicating a likelihood that the pixel subset corresponds to the wear part. The matching criterion is based on processing a labeled set of training images during a training exercise prior to capturing the at least one image of the operating implement.