Systems and methods for automating conversion of drawings to indoor maps and plans

A computer-implemented method of machine learning, the method comprising:

• receiving, by a device, a first set of updates to a first indoor map, the first indoor map previously created by a production machine-learning system having a production map accuracy;
• training, by a device, a supporting machine-learning system using the first set of updates to the first indoor map;
• subsequent to training the support machine-learning system using the first set of updates, applying, by a device, first test data corresponding to the first set of updates to the supporting machine-learning system, wherein the applying results in a first-evaluation indoor map with a first-evaluation map accuracy;
• and
• in response to a determination that the first-evaluation map accuracy is greater than the production map accuracy but not above a predetermined threshold;
• refraining, by a device, from updating the production machine-learning system based on the first set of updates;
• and
• in response to a determination that a second-evaluation map accuracy is greater than the production map accuracy and above the predetermined threshold, updating, by a device, a production machine-learning registry of the production machine-learning system based on both the first set of updates and a second set of updates.

A computer system comprising:

• a processor;
• and
• a memory coupled to the processor, the memory storing instructions that, when executed by the processor, cause the processor to:
• receive a first set of updates to a first indoor map, the first indoor map previously created by a production machine-learning system having a production map accuracy;
• train a supporting machine-learning system using the first set of updates to the first indoor map;
• subsequent to training the support machine-learning system using the first set of updates, apply first test data corresponding to the first set of updates to the supporting machine-learning system, wherein the applying results in a first-evaluation indoor map with a first-evaluation map accuracy;
• and
• in response to a determination that the first-evaluation map accuracy is greater than the production map accuracy but not above a predetermined threshold;
• refrain from updating the production machine-learning system based on the first set of updates;
• and
• in response to a determination that a second-evaluation map accuracy is greater than the production map accuracy and above the predetermined threshold, update a production machine-learning registry of the production machine-learning system based on both the first set of updates and a second set of updates.