Intelligent multi-sensor systems with machine learning and sensor fusion

The Internet of Things (IoT) or cyber-physical systems (CPS) of devices, machines or robots require different, miniaturized types of sensors and systems in order to record the operating environment and ambient conditions in a targeted manner and in real time. In order to “make sense” of the large amount of sensor data, machine learning and sensor fusion methods such as pattern recognition, anomaly detection or classification are used.

This program is concerned with machine learning and sensor fusion concepts for intelligent multisensor systems from scientific data perspectives (such as neural network topologies, deep learning training, validation and testing) as well as system architecture perspectives (such as early or late fusion, feedback loops) in order to amend them for different applications including autonomous driving, drones or smart factories.


Silicon Austria Labs is one of the most exciting research initiatives in Europe. Researching together with SAL means close cooperation along the added-value chain to work on complex problems and research questions relevant to the future. The joint research results will be able to be implemented for the companies (including SMEs).

Are you interested in this program?

Add your project ideas and proposals.

Contact us now