SEAMAL Front - Securely Applied Machine Learning

Project: Research project

Project Details


We want to provide a new and disruptive UWB automotive platform for novel features based on the unique combination of
(i) UWB communication (secure ranging),
(ii) UWB radar (sensing) and
(iii) secure machine learning.
ML and accompanying security measures will be key elements to get more information about possible surrounding targets and to detect, identify and locate only the desired target among others and to provide the respecting applications for authorized users only. The synergetic combination of above techniques will result in a unified device and antenna concept which supports on application level
(i) Secure Car access,
(ii) Inside/Outside Car Detection,
(iii) Live Presence and Gesture Recognition.
- Gesture Recognition provides e.g. individualized support for driver or passengers (like a Kick Sensor). Those features can be combined with secure car access (e.g. identify authorized persons moving towards a car) or supporting e.g. disabled people by transferring movements of a person into a support action when entering the car.
- New applications like life presence detection will enable a car to detect a living being in the car before locking and prevents lock up while alarming the driver.
- In/Outside detection will be supported by both improved ranging and sensing (passenger detection).
We will create a ML methodology that will enable above complex sensing features in a car environment to improve safety and individualized comfort for car occupants.
Effective start/end date1/10/2030/09/23


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.