Deployment of trained neural network based RSS fingerprint dataset
US10716089B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 3, 2019 |
| Grant date | Jul 14, 2020 |
| Priority date | — |
| Expiry date | Jun 3, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W16/20
- WIPO fieldTelecommunications
- WIPO sectorElectrical engineering
Abstract
A method and system of deploying a trained neural network-based RSS fingerprint dataset for mobile device indoor navigation and positioning. The method comprises: based on RSS parameters acquired from a plurality of mobile devices acquired at a set of positions within an indoor area, accumulating the RSS parameters as a trained neural network-based RSS fingerprint dataset in a fingerprint database of the indoor area; and when a density of points represented by the set of positions having accumulated RSS parameters exceeds a deployment threshold density, deploying the RSS fingerprint dataset within a fingerprint map for mobile device navigation of the indoor area, the fingerprint map encompassing the set of positions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.