Abstract: A method and a system are described for detection of anomalies in surfaces, such as pipes. The method includes receiving an input comprising surface material type and plurality of frames of a real-time video stream associated with the surface. The method includes eliminating unwanted frames based on magnitude of 2-Dimensional optical flow vectors of the plurality of frames. The method includes identifying potential anomaly frames based on contours in a dense map created using a magnitude of displacement of each pixel of a frame. The method includes detecting in real-time anomalies in anomaly frames from potential anomaly frames based on trained models selected from a Model Mapping Table. The method includes classifying anomalies in the anomaly frames into anomaly classes using one or more deep learning techniques. The method includes generating a health report comprising anomalies in anomaly frames associated with the surface and providing health report to a user.

Abstract: An apparatus and method for selecting, retaining or bioaugmenting solids in an activated sludge process for improving wastewater treatment using screens. The screens can be used to separate and retain solids based on size, compressibility or shear resistance. The screens are used to separate and select slow growing organisms, faster settling organisms, or materials added to absorb, treat or remove constituents in the activated sludge process. A swapping screen arrangement provides another means of selecting various particles. The exposed shear rate or time, particle compression, or SRTs can be adjusted manually and/or automatically in response to detected readings from an instrument such as a spectrophotometer or other optical approaches to optimize selection of organisms.