Abstract: A clamp assembly for a spool tipping system may comprise a base clamp portion and an adjustable clamp portion. The adjustable clamp portion may be adjustable relative to the base clamp portion based on a flange size of a respective spool. The adjustable clamp portion may be configured to translate through a portion of the base clamp portion and be locked to base clamp portion. The spool tipping system may comprise a lifting system configured to couple to the clamp assembly, lift the clamp assembly and the spool, and transition the spool from a side position to an upright position.

Abstract: Illustrative embodiments are directed to methods and computer systems for reporting unusual or anomalous usage a commodity by consumers. A computer system retrieves a set of usage-information datasets corresponding to a set of consumers, each dataset including past usage of the commodity during at least one of a completed billing period and a current usage of the commodity during the current billing period. The computer system establishes a set of report-trigger conditions for the current billing period, each of the report-trigger conditions corresponding to a consumer. The computer system may monitor usage or spending of the set of consumers to determine, for each consumer, whether an estimated usage established for each consumer fulfills the consumer's report-trigger condition. Once the report-trigger condition is fulfilled, the computer system outputs a report to the consumer.

Abstract: A clamp assembly for a spool tipping system may comprise a base clamp portion and an adjustable clamp portion. The adjustable clamp portion may be adjustable relative to the base clamp portion based on a flange size of a respective spool. The adjustable clamp portion may be configured to translate through a portion of the base clamp portion and be locked to base clamp portion. The spool tipping system may comprise a lifting system configured to couple to the clamp assembly, lift the clamp assembly and the spool, and transition the spool from a side position to an upright position.

Abstract: Illustrative embodiments of the present invention are directed to methods and computer systems for reporting a consumer's usage of a resource. A computer system retrieves consumer characteristic data and resource usage data for the first consumer and a set of second consumers including characteristic data related to each consumer. The computer system selects at least one consumer that is similar to the first consumer from the set of second consumers based upon a plurality of common criteria between the first consumer's characteristic data and a second consumer's characteristic data. The computer processes may be performing iteratively until the total number of similar consumers is equal to or greater than the predetermined number of consumers. Once a desired number of similar consumers is found, the computer system generates a report that displays the first consumer's resource usage data and the at least one similar consumers' resource usage data.

Abstract: Illustrative embodiments are directed to methods and computer systems for reporting unusual or anomalous usage a commodity by consumers. A computer system retrieves a set of usage-information datasets corresponding to a set of consumers, each dataset including past usage of the commodity during at least one of a completed billing period and a current usage of the commodity during the current billing period. The computer system establishes a set of report-trigger conditions for the current billing period, each of the report-trigger conditions corresponding to a consumer. The computer system may monitor usage or spending of the set of consumers to determine, for each consumer, whether an estimated usage established for each consumer fulfills the consumer's report-trigger condition. Once the report-trigger condition is fulfilled, the computer system outputs a report to the consumer.

Abstract: Illustrative embodiments of the present invention are directed to methods and computer systems for reporting unusual or anomalous usage or spending of a commodity by consumers. A computer system retrieves a set of usage-information datasets corresponding to a set of consumers, each dataset including past usage of the commodity during at least one of a completed billing period and a current usage of the commodity during the current billing period. The computer system establishes a set of report-trigger conditions for the current billing period, each of the report-trigger conditions corresponding to a consumer. The computer system monitor usage or spending of the set of consumers to determine, for each consumer, whether an estimated usage established for each consumer fulfills the consumer's report-trigger condition. Once the report-trigger condition is fulfilled, the computer system outputs a report to the consumer.

Abstract: Multiple instances of a distributed application are run in a Kubernetes cluster. An updated version of the application must undergo some post-launch initialization before a production workload handled by the original version can be switched to the updated version. Accordingly, a temporary update-monitor pod is inserted into the cluster so that it can query the application as to its update status and report it to a log file. A script external to the cluster can read the log file to determine if initialization is complete. If so, the workload can be switched to the update instance. The temporary update-monitor pod is destroyed to free up resources and to ensure that it is does not pose a security vulnerability.

Abstract: Multiple instances of a distributed application are run in a Kubernetes cluster. An updated version of the application must undergo some post-launch initialization before a production workload handled by the original version can be switched to the updated version. Accordingly, a temporary update-monitor pod is inserted into the cluster so that it can query the application as to its update status and report it to a log file. A script external to the cluster can read the log file to determine if initialization is complete. If so, the workload can be switched to the update instance. The temporary update-monitor pod is destroyed to free up resources and to ensure that it is does not pose a security vulnerability.

Abstract: Techniques for unusual usage alerts without smart meter data are provided. The computing device can determine a set of climate control disaggregation coefficients and obtain weather data corresponding to at least a portion of a billing period. In turn, the computing device can determine first forecasted usage data for the at least a portion of the billing period based on the set of climate control disaggregation coefficients and the weather data, and determine second forecasted usage data for a length of the billing period based at least in part on the first forecasted usage data. In some aspects, the computing device can project unusual energy usage for the billing period based on the second forecasted usage data determined to be greater than usage data for a prior time period. The computing device can generate an alert notification including an indication of the unusual energy usage projection.

Abstract: An occupancy schedule determining method and system that receives usage data indicating a quantity of a resource supplied by a utility that is used at the location over a plurality of days, each of the plurality of days being subdivided into a plurality of predetermined time periods, and the usage data indicating the quantity of the resource supplied by the utility that is used during each of the predetermined time periods, aggregates the usage data for each of the plurality of predetermined time periods over the plurality of days, and uses the aggregated usage data to determine the occupancy schedule at the location using a processor.

Abstract: A thermostat set point estimation method and system that selects a plurality of candidate thermostat set points, determines for each of the plurality of candidate thermostat set points a predicted energy usage amount corresponding to the candidate thermostat set point, determines for each of the plurality of candidate thermostat set points an error value corresponding to the candidate thermostat set point using an actual energy usage amount and the predicted energy usage amount corresponding to the candidate thermostat set point, and identifies an estimated thermostat set point by selecting the candidate thermostat set point having the error value that is lowest from the plurality of candidate thermostat set points.

Abstract: Methods and computer systems are disclosed for identifying the power-demand of a climate-control system at a premises to reduce usage of energy at the premises. A computer system receives energy usage data and run-time data of the climate-control system. The operational data includes an on-time and/or off-time associated with the climate-control system. The computer system determines a power-draw of the climate-control system using the energy usage data and the run-time data and outputs the power-draw to be used to reduce the energy usage at the premises.

Abstract: The disclosure provides a computer-implemented method and system of reducing commodity usage by providing tailored consumer information to the consumer. The method utilizes neural network and machine learning techniques to calculate and cluster statistical data to classify the premises for desired observable condition, including the presence of a programmed thermostat. A score is determined that corresponds to at least one of: (i) a present state of an observable condition, (ii) a non-present state of the observable condition, and (iii) a degree of a condition of the observable condition, to provide tailored consumer information associated to the consumer's usage of the commodity.

Abstract: Techniques for unusual usage alerts without smart meter data are provided. The computing device can determine a set of climate control disaggregation coefficients and obtain weather data corresponding to at least a portion of a billing period. In turn, the computing device can determine first forecasted usage data for the at least a portion of the billing period based on the set of climate control disaggregation coefficients and the weather data, and determine second forecasted usage data for a length of the billing period based at least in part on the first forecasted usage data. In some aspects, the computing device can project unusual energy usage for the billing period based on the second forecasted usage data determined to be greater than usage data for a prior time period. The computing device can generate an alert notification including an indication of the unusual energy usage projection.

Abstract: Methods and computer systems are disclosed for identifying the power-demand of a climate-control system at a premises to reduce usage of energy at the premises. A computer system receives energy usage data and run-time data of the climate-control system. The operational data includes an on-time and/or off-time associated with the climate-control system. The computer system determines a power-draw of the climate-control system using the energy usage data and the run-time data and outputs the power-draw to be used to reduce the energy usage at the premises.

Abstract: The disclosure provides a computer-implemented method and system of reducing commodity usage by providing tailored consumer information to the consumer. The method utilizes neural network and machine learning techniques to calculate and cluster statistical data to classify the premises for desired observable condition, including the presence of a programmed thermostat. A score is determined that corresponds to at least one of: (i) a present state of an observable condition, (ii) a non-present state of the observable condition, and (iii) a degree of a condition of the observable condition, to provide tailored consumer information associated to the consumer's usage of the commodity.

Abstract: Illustrative embodiments of the present invention are directed to methods and computer systems for reporting unusual or anomalous usage or spending of a commodity by consumers. A computer system retrieves a set of usage-information datasets corresponding to a set of consumers, each dataset including past usage of the commodity during at least one of a completed billing period and a current usage of the commodity during the current billing period. The computer system establishes a set of report-trigger conditions for the current billing period, each of the report-trigger conditions corresponding to a consumer. The computer system monitor usage or spending of the set of consumers to determine, for each consumer, whether an estimated usage established for each consumer fulfills the consumer's report-trigger condition. Once the report-trigger condition is fulfilled, the computer system outputs a report to the consumer.

Abstract: Illustrative embodiments of the present invention are directed to methods and computer systems for reporting a consumer's usage of a resource. A computer system retrieves consumer characteristic data and resource usage data for the first consumer and a set of second consumers including characteristic data related to each consumer. The computer system selects at least one consumer that is similar to the first consumer from the set of second consumers based upon a plurality of common criteria between the first consumer's characteristic data and a second consumer's characteristic data. The computer processes may be performing iteratively until the total number of similar consumers is equal to or greater than the predetermined number of consumers. Once a desired number of similar consumers is found, the computer system generates a report that displays the first consumer's resource usage data and the at least one similar consumers' resource usage data.