Motion detection based on machine learning of wireless signal properties
US10108903B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 8, 2017 |
| Grant date | Oct 23, 2018 |
| Priority date | — |
| Expiry date | Dec 8, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01S13/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In a general aspect, motion in a space can be detected based on machine learning of wireless signal properties. In some aspects, sets of tagged neural network input data are obtained at a neural network training system. Each set of tagged neural network input data is based on a statistical analysis of a series of wireless signals transmitted through a space over a respective time period, and each set of the tagged neural network input data includes a tag indicating whether motion occurred in the space over the respective time period. The sets of tagged neural network input data are processed by the neural network training system to parameterize nodes of a neural network system. Parameterizing the nodes configures the neural network system to detect motion based on untagged neural network input data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.