KI-Auto-Net identifies the needs and challenges of industry in order to operate campus networks much more easily, efficiently, and economically with the help of Artificial Intelligence (AI) and Digital Twins. Communication networks in industrial environments must meet high requirements in terms of reliability, security, latency, and throughput. 5G campus networks—private mobile networks tailored to specific business needs—provide companies with a powerful and flexible communications infrastructure. At the same time, however, they place high demands on network planning and management.
Project Objective KI-Auto-Net identifies industrial needs and challenges to enable significantly simpler, more efficient, and more cost-effective operation of campus networks through the use of Artificial Intelligence (AI) and Digital Twins. The project focuses on:
- Automating network planning, operation, and optimization,
- Reducing complexity and operating costs,
- Lowering market entry barriers, particularly for small and medium-sized enterprises (SMEs).
A key outcome of the project is a strategic roadmap for “Digital Twins for German Industries”, paving the way for the widespread adoption of AI-supported, automated network solutions.
Methodology
The KI-Auto-Net project systematically captures industrial requirements in a practical and application-oriented manner. This is achieved through a combination of sector analyses, stakeholder mapping, interactive workshops, structured questionnaires, feedback evaluations, and in-depth interviews. The findings are incorporated into the strategic roadmap and translated into concrete recommendations for industry and policymakers.
Opportunities for Companies to Participate
KI-Auto-Net relies on close collaboration with companies to develop practical, demand-driven recommendations for action. Contribute your perspectives and actively help shape the future of intelligent campus networks.
Partners
- DFKI GmbH
- Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS
