Intelligent Ultra Low-Power Signal Processing for Automotive
While traditional cars relied solely on the senses of their drivers – mostly their eyes and ears –, the cars of today are equipped with more and more sensors, supplying information to their drivers or using the information to take decision autonomously. Yet, to become truly aware of their environment, such smart cars are still missing an invaluable input on which we, as humans, rely strongly: the acoustic information. The I-SPOT Project, in which this thesis in inserted, targets the addition of acoustic sensing technology to bring enhanced environmental awareness in cars. The goal of the I-SPOT project is to drive such acoustic awareness of smart cars by enabling sensing, localising and analysing environmental audio signals during the active (drive) and passive (park) car mode. This thesis will therefore investigate the efficient placement of audio sensors on the car body to improve the received signal quality, and the development of low-footprint signal processing technologies for automotive acoustic signal characterisation and localisation. In particular, both traditional signal processing methods and machine learning based algorithms will be studied and developed.
Period: Oct. 2020 – Sep. 2023
Funding: Research Executive Agency of the European Commission (H2020 Marie Skłodowska-Curie European Industrial Doctorates), Grant Agreement No. 956962
Budget: 513 kEUR
Partners:
- KU Leuven
- Robert Bosch GmbH
People:
- Stefano Damiano (PhD Student)
- Toon van Waterschoot (Supervisor)