Abstract: Systems and methods to label images for inclusion into a machine learning image recognition training data set. A coded labeling definition is defined. A set of digital images is collected that includes images of different types of piece of equipment. A digital image is presented that includes an image of a particular piece of equipment. A received numeric code corresponding to the particular piece of equipment within the present image is received. The received numeric code is associated with the present image and the present image is stored in association with the received numeric code into a machine learning image recognition data set. A machine learning image recognition is trained based on the machine learning image recognition data set to automatically associate unlabeled images with the respective numeric code that corresponds to the particular piece of equipment in the unlabeled image.

Abstract: A system and method is disclosed for using AMI smart meter messaging types and data mining decision trees to determine if local equipment failure is present. The system and method may be used to predict impending failure based upon smart meter message behaviors and to create proactive investigation tickets. The predictions models may be generated from a database of smart meter messaging and customer outage reports. The system and method can be applied to detect failures of higher level device equipment and may be incorporated into customer service processes. The system and method may also be used to determine customer owned equipment failures for referral to electricians.

Abstract: Systems and methods to label images for inclusion into a machine learning image recognition training data set. A coded labeling definition is defined. A set of digital images is collected that includes images of different types of piece of equipment. A digital image is presented that includes an image of a particular piece of equipment. A received numeric code corresponding to the particular piece of equipment within the present image is received. The received numeric code is associated with the present image and the present image is stored in association with the received numeric code into a machine learning image recognition data set. A machine learning image recognition is trained based on the machine learning image recognition data set to automatically associate unlabeled images with the respective numeric code that corresponds to the particular piece of equipment in the unlabeled image.

Abstract: A system and method is disclosed for using AMI smart meter messaging types and data mining decision trees to determine if local equipment failure is present. The system and method may be used to predict impending failure based upon smart meter message behaviors and to create proactive investigation tickets. The predictions models may be generated from a database of smart meter messaging and customer outage reports. The system and method can be applied to detect failures of higher level device equipment and may be incorporated into customer service processes. The system and method may also be used to determine customer owned equipment failures for referral to electricians.

Abstract: A system and method is disclosed for using AMI smart meter messaging types and data mining decision trees to determine if local equipment failure is present. The system and method may be used to predict impending failure based upon smart meter message behaviors and to create proactive investigation tickets. The predictions models may be generated from a big database of smart meter messaging and customer outage reports. The system and method can be applied to detect failures of higher level device equipment and may be incorporated into customer service processes. The system and method may also be used to determine customer owned equipment failures for referral to electricians.