[MA] Development of a Modular Monitoring System for Advanced Driver Assistance Systems (ADAS)

In the rapidly evolving field of Advanced Driver Assistance Systems (ADAS), the ability to effectively monitor, compare, and analyze data is critical to improving performance and ensuring safety. This thesis proposes the development of a comprehensive monitoring system tailored for ADAS applications, leveraging advanced data mining techniques and DevOps practices.

The core of the system will be a modular framework designed to facilitate flexible and scalable integration of various data sources and analytics tools. This approach ensures that the system can easily adapt to the dynamic requirements of ADAS, providing robust capabilities for real-time monitoring and data comparison.

The monitoring system will feature intuitive data visualization tools to present key insights and performance metrics, aiding developers and engineers in making informed decisions. By applying distributed systems engineering principles, this project aims to deliver a reliable, scalable, and robust solution, advancing the state-of-the-art in ADAS performance evaluation and monitoring.

Betreuer: Sebastian Götz