Scalable data discovery in an internet of things (IoT) system
US10257678B2 · kind B2 · utility
8Cited by
1References
18Claims
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Key dates
| Filing date | May 20, 2015 |
| Grant date | Apr 9, 2019 |
| Priority date | — |
| Expiry date | May 31, 2035 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W84/18
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Data discovery for sensor data in an M2M network uses probabilistic models, such as Gaussian Mixing Models (GMMs) to represent attributes of the sensor data. The parameters of the probabilistic models can be provided to a discovery server (DS) that respond to queries concerning the sensor data. Since the parameters are compressed compared to the attributes of the sensor data itself, this can simplify the distribution of discovery data. A hierarchical arrangement of discovery servers can also be used with multiple levels of discovery servers where higher level discovery servers using more generic probabilistic models.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.