公开(公告)号：US20210403004A1

公开(公告)日：2021-12-30

申请号：US17471411

申请日：2021-09-10

Applicant: Intel Corporation

Inventor： Ignacio J. Alvarez ,  Marcos Carranza ,  Ralf Graefe ,  Francesc Guim bernat ,  Cesar Martinez-spessot ,  Dario Oliver ,  Selvakumar Panneer ,  Michael Paulitsch ,  Rafael Rosales

IPC: B60W40/09 ,  G06K9/62 ,  G06N20/00 ,  H04W4/40

Abstract: Techniques are disclosed to address issues related to the use of personalized training data to supplement machine learning trained models for Driver Monitoring System (DMS), and the accompanying mechanisms to maintain confidentiality of this personalized training data. The techniques disclosed herein also address issues related to maintaining transparency with respect to collected sensor data used in a DMS. Additionally, the techniques disclosed herein facilitate the generation of a digital representation of a driver for use as supplemental training data for the DMS machine learning trained models, which allow for DMS algorithms to be tailored to individual users.

公开(公告)号：US10992752B2

公开(公告)日：2021-04-27

申请号：US16368231

申请日：2019-03-28

Applicant: Intel Corporation

Inventor： Ralf Graefe ,  Florian Geissler

IPC: H04L29/08 ,  H04Q9/00 ,  H04W4/029 ,  H04W4/40 ,  H04W84/18 ,  H04W4/38

Abstract: Systems, methods, and computer-readable media are provided for wireless sensor networks (WSNs), including sensor deployment mechanisms for road surveillance. Disclosed embodiments are applied to design roadside infrastructure with optimal perception for a given geographic area. The deployment mechanisms account for the presence of static and dynamic obstacles, as well as symmetry aspects of the underlying environment. The deployment mechanisms minimize the number of required sensors to reduce costs and conserve compute and network resources, and extended infrastructure the sensing capabilities of sensor networks. Other embodiments are disclosed and/or claimed.