Abstract: The present invention relates to system and method for providing near real-time DR events and price signals to the customer end-points to optimally manage the available DR resources. The system utilizes bottom up load forecasting for accurate individualized forecasts for customer loads in the presence of dynamic pricing signals. For better efficiency and reliability of grid operation the system utilizes advanced machine learning and robust optimization techniques for real-time and “personalized” DR-offer dispatch.

Abstract: The present invention relates to a signal processing technique for characterization of baseline noise, and for determining load reduction in presence of baseline noise. The method utilizes sparse signal processing algorithm to recover demand resource response signal and a plurality of SNR enhancement strategies are then applied to demand resource response signal for enhancing the signal to noise ratio.

Abstract: The disclosure includes a system and method for distinguishing objects of similar appearance that vary in color. An image recognition application receives a query image of a plurality of objects, determines a candidate list of indexed images that match an object in the query image based on luminance features, crops an image of the object from the query image to generate a cropped image, computes color features for the object, ranks the candidate list of indexed images based on the color features, and provides the candidate list of indexed images to a user.

Abstract: A system and method that computes a quality score for an index image is disclosed. The method includes receiving an index image, computing a blurriness score of the index image based on variance associated with the index image, computing an image resolution score of the index image based on an area of the index image and a threshold area, computing a feature spread score for the index image using a first plurality of features associated with the index image, computing a feature uniqueness score for the index image using a description associated with each of a second plurality of features and determining a quality score for the index image using the blurriness score, the image resolution score, the feature spread score, and the feature uniqueness score.

Abstract: The disclosure includes a system and method for distinguishing objects of similar appearance that vary in color. An image recognition application receives a query image of a plurality of objects, determines a candidate list of indexed images that match an object in the query image based on luminance features, crops an image of the object from the query image to generate a cropped image, computes color features for the object, ranks the candidate list of indexed images based on the color features, and provides the candidate list of indexed images to a user.

Abstract: A system and method that computes a quality score for an index image is disclosed. The method includes receiving an index image, computing a blurriness score of the index image based on variance associated with the index image, computing an image resolution score of the index image based on an area of the index image and a threshold area, computing a feature spread score for the index image using a first plurality of features associated with the index image, computing a feature uniqueness score for the index image using a description associated with each of a second plurality of features and determining a quality score for the index image using the blurriness score, the image resolution score, the feature spread score, and the feature uniqueness score.

Abstract: The present invention relates to a signal processing technique for characterization of baseline noise, and for determining load reduction in presence of baseline noise. The method utilizes sparse signal processing algorithm to recover demand resource response signal and a plurality of SNR enhancement strategies are then applied to demand resource response signal for enhancing the signal to noise ratio.

Abstract: A scalable and web-based demand response platform for optimization and management of Demand response resources are provided. The optimization and management are achieved by using a server, a program design module, a customer portal module, a forecasting optimization module, an event management module, an application programming interface, an analytics module for performing analysis for performing analysis of the data feeds. The said platform is offered to the users on software-as-a-service model.

Abstract: The present invention relates to system and method for providing near real-time DR events and price signals to the customer end-points to optimally manage the available DR resources. The system utilizes bottom up load forecasting for accurate individualized forecasts for customer loads in the presence of dynamic pricing signals. For better efficiency and reliability of grid operation the system utilizes advanced machine learning and robust optimization techniques for real-time and “personalized” DR-offer dispatch.

Abstract: A system and a method for optimization and management of Demand Response in real time manner is provided. The system employs a resource modeler, a forecasting engine, an optimizer, a dispatch engine, and a baseline engine. The system is built using open framework standards based signaling and data collection, and is offered under a “Software-as-a-Service” model to significantly reduce the cost of participation in demand response. It uses off the shelf information and communication technology (ICT) and controls equipment.