Deployment of trained neural network based RSS fingerprint dataset

A server computing system for deploying a received signal strength (RSS) fingerprint dataset, based on a trained neural network for mobile device indoor navigation, the server computing system comprising:

• a processor;
• and
• a memory including instructions executable in the processor to:
• receive RSS parameters from a plurality of mobile devices, the RSS parameters acquired for a set of positions within an indoor area, the RSS parameters being determined by the plurality of mobile devices using a respective RSS sensor device;
• train a neural network implemented in the processor at least in part based on the RSS parameters, the neural network comprising a first neural network layer corresponding to a set of RSS input parameters for a wireless signal in accordance with a first wireless communication protocol, and at least a second neural network layer corresponding to the set of RSS input parameters for the wireless signal in accordance with at least a second wireless communication protocol, an RSS input parameter being based on a postulated RSS model;
• when a density of points represented by the set of positions having the RSS parameters exceeds a deployment threshold density, deploy the RSS fingerprint dataset within a fingerprint map, based on the trained neural network, the fingerprint map encompassing the set of positions;
• and
• navigate another mobile device in the indoor area using the deployed RSS fingerprint dataset within the fingerprint map.