Computer-implemented method and system for identifying and assessing infrastructure equipment based on analysis of a digitial representation of a geogprahic region using artificial intelligence (ai) and image processing and analysis

A computer-implemented method of evaluating and updating a machine learning (ML) model for virtual auditing of infrastructure equipment based on rules associated with characteristics of the infrastructure equipment, the method comprising:

• receiving, by a virtual audit application stored in non-transitory memory of a computer system and executable by a processor of the computer system, a type of equipment to be audited and a geographic region;
• retrieving, by the virtual audit application, a plurality of images of the geographic region;
• analyzing, by the virtual audit application, using one or more ML models, the plurality of images to identify and classify assets associated with the equipment, wherein the analyzing comprises:
• processing a first image of the plurality of images using a first ML model of the one or more ML models to identify a first asset of the assets;
• determining, by an ML model training application stored in the non-transitory memory of the computer system and executable by the processor of the computer system, that the first ML model fails to identify one or more other assets associated with the equipment based on rules associated with characteristics of the equipment;
• and
• updating, by the ML model training application, based on the determining, one or more parameters of the first ML model.

A computer-implemented method of updating an audit of infrastructure in a geographic region by analyzing a digital representation of the geographic region using artificial intelligence (AI) and computer image processing and analysis, the method comprising:

• receiving, by a virtual audit application stored in non-transitory memory of a computer system and executable by a processor of the computer system, a type of equipment to be audited, a geographic region, and a previous audit record of the type of equipment in the geographic region;
• determining, by the virtual audit application, a route in the geographic region;
• retrieving, by the virtual audit application, from a geographic image database, first image acquisition timestamp information associated with a plurality of first images corresponding respectively to a plurality of locations along the route;
• comparing, by the virtual audit application, the first image acquisition timestamp information to second image acquisition timestamp information associated with a plurality of second images of assets associated with the equipment identified at the plurality of locations in the previous audit record;
• determining, by the virtual audit application, based on the comparing, that at least one of the plurality of first images associated with a first location of the plurality of locations is acquired more recently than a respective one of the plurality of second images associated with the same first location;
• analyzing, by the virtual audit application, using one or more machine learning (ML) models, the at least one of the plurality of first images that is acquired more recently to identify and classify assets associated with the equipment;
• and
• updating, by the virtual audit application, the previous audit record based on information about the assets identified from the at least one of the plurality of first images that is acquired more recently.