Data analytics for predictive maintenance

A system for predicting asset failure in an electrical distribution system comprising:

• a first asset,
• a first electrical meter,
• a second asset,
• a second electrical meter,
• an artificial intelligence (AI) model, and
• one or more computers comprising one or more processors and one or more non-transitory computer readable media, the one or more non-transitory computer readable media including program instructions stored thereon that when executed cause the one or more computers to:
• receive, by the one or more processors, first meter data from the first electrical meter;
• associate, by the one or more processors, the first meter data with the first asset to create first asset data;
• receive, by the one or more processors, second meter data from the second electrical meter;
• associate, by the one or more processors, the second meter data with the second asset to create second asset data;
• send, by the one or more processors, the first asset data and the second asset data to the AI model;
• output, by the AI model, a first asset designation comprising a first designation of the first asset as a first match or a first non-match for a condition;
• and
• output, by the AI model, a second asset designation comprising a second designation of the second asset as a second match or a second non-match for the condition.

A method for creating an artificial intelligence model to predict asset failure in an electrical distribution system comprising the steps of:

• receiving first meter data from a first electrical meter;
• associating the first meter data with a first asset to create first asset data;
• receiving second meter data from a second electrical meter;
• associating the second meter data with a second asset to create second asset data;
• designating the first asset data as a first match or a first non-match for a condition;
• and
• sending the first asset data and the second asset data to an artificial intelligence (AI) model as a training set;
• outputting a result of a decision analysis by the AI model, the results comprising a match designation or a non-match designation for the condition for the second asset;
• generating a graphical user interface comprising the result;
• generating an input for changing the result to create a changed result;
• and
• sending the changed result to the AI model to improve the decision analysis.