Crowd-sourced training of a neural network for RSS fingerprinting
US10671921B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | May 1, 2019 |
| Grant date | Jun 2, 2020 |
| Priority date | — |
| Expiry date | May 1, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/044
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and system of crowd-sourced training of a neural network for mobile device indoor navigation and positioning. The method, executed in a processor of a server computing device, comprises: based on RSS parameters acquired at a mobile device from a wireless signal source, localizing the mobile device to a first position within indoor area in accordance with a probabilistic confidence level; if the confidence level exceeds a threshold confidence level, adding the RSS parameters in association with the first position to a fingerprint database of the indoor area; and training a neural network implemented in the processor at least in part based on the RSS parameters as added to the fingerprint database.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.