Systems and methods for dynamic mapping and routing using machine learning

A computing system comprising:

• one or more processors;
• and
• one or more non-transitory, computer-readable media storing instructions that are executable by the one or more processors to cause the computing system to perform operations, the operations comprising:
• accessing data indicative of a plurality of items;
• accessing map data indicative of a layout of an indoor location;
• correlating, based on the map data, an identifier associated with each of the plurality of items with an initial location within the indoor location;
• obtaining, over a network, one or more data signals generated by a mobile computing device located within the indoor location, wherein the one or more data signals are based on motion of the mobile computing device;
• processing, using a machine-learned model, the one or more data signals from the mobile computing device located within the indoor location, wherein processing the one or more data signals comprises determining, contextual information indicative of a level of activity associated with the indoor location;
• based on the map data, the initial location, and the contextual information, iteratively generating a route segment within the indoor location, wherein the route segment indicates a path to a respective item of the plurality of items within the indoor location;
• and
• outputting a command instruction to generate a user interface that displays the route segment.

A computer-implemented method comprising:

• accessing, by a computing system, data indicative of a plurality of items;
• accessing, by the computing system, map data indicative of a layout of an indoor location;
• correlating, by the computing system and based on the map data, an identifier associated with each of the plurality of items with an initial location within the indoor location;
• generating, by the computing system and based on the map data and the initial location, a first route segment to a first location of a first item within the indoor location;
• outputting, by the computing system, a command instruction to generate a user interface that indicates the first route segment and the first location of the first item within the indoor location;
• obtaining, over a network, one or more data signals generated by a mobile computing device located within the indoor location, wherein the one or more data signals are based on motion of the mobile computing device;
• processing, by the computing system using a machine-learned model, the one or more data signals from the mobile computing device located within the indoor location, wherein processing the one or more data signals comprises determining, contextual information indicative of a level of activity associated with the indoor location;
• generating, by the computing system and based on the map data and the contextual information, a second route segment from the first location to a second location of a second item within the indoor location;
• receiving, by the computing system, user input data indicating the first item was selected or disregarded;
• and
• based on receiving the user input data, outputting, by the computing system, a command instruction to display the second route segment and the second location of the second item within the indoor location.