Indoor Localization Based on Multiple Device Sensors

A computer-implemented method comprising:

• obtaining location data associated with a first computing device and a second computing device, the location data indicative of the first computing device and the second computing device each being at a target location;
• in response to obtaining the location data, determining an on-user device status for the each of the first and second computing devices;
• in response to determining an on-user device status for each of the first and second computing devices, obtaining inertial measurement unit (IMU) sensor data from each of the first and second computing device;
• inputting the IMU sensor data from each of the first and second computing devices into a machine learned model, wherein the machine learned model is configured to combine the IMU sensor data from each of the first and second computing devices;
• obtaining, from the machine learned model, output data indicative of a predicted location;
• comparing the output data indicative of the predicted location to data indicative of a location of a target subzone;
• and
• in response to obtaining data indicative of colocation of each of the first and second computing devices within the target subzone of the target location, transmitting data which instructs a user interface of the first computing device to provide a content item for display.

A non-transitory computer readable medium embodied in a computer-readable storage device and comprising instructions that, when executed by a processor, cause the processor to perform operations, the operations comprising:

• obtaining location data associated with a first computing device and a second computing device, the location data indicative of the first computing device and the second computing device each being at a target location;
• in response to obtaining the location data, determining an on-user device status for the each of the first and second computing devices;
• in response to determining an on-user device status for each of the first and second computing devices, obtaining inertial measurement unit (IMU) sensor data from each of the first and second computing devices;
• inputting the IMU sensor data from each of the first and second computing devices into a machine learned model, wherein the machine learned model is configured to combine the IMU sensor data from each of the first and second computing devices;
• obtaining, from the machine learned model, output data indicative of a predicted location;
• comparing the output data indicative of the predicted location to data indicative of a location of a target subzone;
• and
• in response to obtaining data indicative of colocation of each of the first and second computing devices within the target subzone of the target location, transmitting data which instructs a user interface of the first computing device to provide a content item for display.