Remote diagnosis of energy or resource-consuming devices based on usage data

A computing system for determining an efficiency of a physical household appliance, comprising:

• a processor;
• and
• a memory storing instructions that, when executed by the processor, cause the system to perform:
• sensing, by the computing system, appliance usage data associated with the physical household appliance from one or more sensors, wherein the appliance usage data comprises data of different sources, wherein the data of different sources comprises messages or signals including codes;
• transforming, by the computing system, the appliance usage data into a standardized format compatible with object based data structures, wherein the transforming comprises normalizing the appliance usage data into a time series format;
• storing the transformed appliance usage data in the standardized format in a data source;
• determining, by a machine learning model, one or more attributes, selected from candidate attributes identifying a property of a material, an environmental parameter, or an energy parameter associated with the appliance or a facility at which the physical household appliance is located, that distinguish an efficient operation of the appliance from an inefficient operation, wherein the determining of the one or more attributes comprises:
• selecting a first attribute having a highest individual diagnosis capability compared to other candidate attributes;
• iteratively scoring other attributes besides the first attribute based on respective combined diagnosis capabilities of each of the other attributes when combined with the first attribute;
• and
• selecting a second attribute from the other attributes based on the iterative scoring, wherein a combined diagnosis capability of the second attribute is different from an individual diagnosis capability of the second attribute by itself;
• generating, by the computing system based on the selected first attribute and the selected second attribute, an indication of whether to perform a repair or a maintenance on the physical household appliance;
• and
• in response to generating an indication to perform a repair or a maintenance, selectively implementing a physical shutdown of the physical household appliance.

A non-transitory computer-readable medium of a computing system for determining an efficiency of a physical household appliance, the non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the computer system to perform:

• sensing appliance usage data associated with the physical household appliance from one or more sensors, wherein the appliance usage data comprises data of different sources, wherein the data of different sources comprises messages or signals including codes;
• transforming the appliance usage data into a standardized format compatible with object based data structures, wherein the transforming comprises normalizing the appliance usage data into a time series format;
• storing the transformed appliance usage data in the standardized format in a data source;
• determining, by a machine learning model, one or more attributes, selected from candidate attributes identifying a property of a material, an environmental parameter, or an energy parameter associated with the physical household appliance or a facility at which the physical household appliance is located, that distinguish an efficient operation of the physical household appliance from an inefficient operation, wherein the determining of the one or more attributes comprises;
• selecting a first attribute having a highest individual diagnosis capability compared to other candidate attributes;
• iteratively scoring other attributes besides the first attribute based on respective combined diagnosis capabilities of each of the other attributes when combined with the first attribute;
• and
• selecting a second attribute from the other attributes based on the iterative scoring, wherein a combined diagnosis capability of the second attribute is different from an individual diagnosis capability of the second attribute by itself;
• generating, by the computing system based on the selected first attribute and the selected second attribute, an indication of whether to perform a repair or a maintenance on the physical household appliance;
• and
• in response to generating an indication to perform a repair or a maintenance, selectively implementing a physical shutdown of the physical household appliance.