Electronic device identification using emitted electromagnetic signals
US12309878B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 21, 2024 |
| Grant date | May 20, 2025 |
| Priority date | — |
| Expiry date | Jun 21, 2044 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W84/12
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Machine learning-based methods are disclosed to identify the types of electronic devices present in an area using emitted passive electromagnetic signals (e.g., RF signals such as Bluetooth, WiFi, and/or cellular). The identification of the electronic devices improves private and public security in determining human presence and device presence. The disclosed methods use trained machine learning models that learn the relationship between the metadata present within the broadcast electromagnetic signals and the types of electronic devices present. The disclosed methods, apparatuses and systems can include use of several wireless data transfer protocols, such as Wi-Fi, Bluetooth and cellular.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.