Self-learning connected-device network
US11356537B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Mar 11, 2019 |
| Grant date | Jun 7, 2022 |
| Priority date | — |
| Expiry date | Apr 14, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W4/70
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A connected-device network can continually learn from abstract sensory data (e.g., speech processing, cognitive inference, and/or computer vision image segmentation) and can generate never-seen-before data in real time. In one aspect, the network devices extract important correlations in the sensor data based on network data collected at different time slice and/or locations. Further, underlying relationships in a set of data can be detected as the sensor data transverses through different layers of the network. Moreover, the network devices can provide logic in different layers to help classify the sensor data early in the detection process (e.g., instead of waiting for it to reach its final destination).
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.