Adaptive Network Planning Tool: Campus Network with ADAPT

High-bay racks whose occupancy changes daily. Production islands that are spontaneously set up and dismantled. Autonomous robots that continuously send and receive data. Modern production and intralogistics environments are highly dynamic and thus place entirely new demands on wireless communication networks. Traditional campus network planning is not designed for these challenges, as once installed, wireless infrastructure is static and adjustments are resource-intensive. ADAPT addresses this issue by developing a network planning and operations tool that treats 5G/6G campus networks–closely integrated with production and logistics–as an adaptive and secure communication infrastructure.

The image shows a stylized blue diagram of a connected 5G campus network, with a large “5G” symbol at its center, from which lines lead to various ICONS such as a factory, an airplane, a house, a truck, and location markers.
© Tierney - stock.adobe.com

Project goal: adaptive campus network for dynamic requirements

ADAPT aims to develop a comprehensive tool that supports companies in not only planning their 5G/6G campus networks once, but also in continuously, automatically, and securely adapting them to dynamic operational requirements. 

The focus is on: 

  • automated, resilient, and secure communication in highly dynamic environments 
  • real-time adaptation of the campus network to changing processes, structures, and material flows
  • more efficient, secure, and cost-effective production and logistics processes  

 ADAPT covers the entire lifecycle–from initial network planning through ongoing operations to continuous optimization. 

Project profile

Project titel ADAPT - Adaptive, Dynamic Network Planning and Operation Concepts for Partially and Fully Automated Production and Intralogistics
Duration

January 2026 to December 2028

Funding VOLUME approximately €2.8 million  
Funder Ministry of Economic Affairs, Industry, Climate Protection, and Energy of the State of North Rhine-Westphalia
Cooperation partners

KRONE, Fraunhofer IML 

Techbros GmbH 

PHYSEC GmbH 

Dortmund University of Technology  

Ruhr University Bochum

Project ManagEment Fraunhofer Institute for Material Flow and Logistics

“With ADAPT, the campus network transforms from a rigid supply network into an adaptive, AI-supported infrastructure: a network planning tool that efficiently, securely, and in real time adapts 5G/6G campus networks in production and intralogistics to dynamic requirements.”
Frido Feldmeier, Research Scientist at Fraunhofer IML in Dortmund

The solution: hybrid digital twins, ai, and campus network security

The ADAPT project combines four key components for the campus network: 

  • Hybrid digital twins:  
    High-performance simulation software models production facilities, logistics structures, and material flows as a hybrid digital twin. This allows network planning, load scenarios, and adaptation strategies to be tested, evaluated, and optimized in advance before being implemented in the real-world environment. The digital twin continuously receives real-time feedback from operations, enabling continuous, iterative improvement of the overall system. 
  • AI-powered network optimization:  
    AI models are used to automate channel modeling and network planning. Artificial intelligence evaluates configurations in real time, detects changes in radio field propagation—such as those caused by shadowing—and automatically initiates optimization measures. 
  • Mobile Radio Units: 
    To respond flexibly to connectivity bottlenecks caused by changes in the environment or temporary spikes in data traffic, ADAPT breaks away from the concept of fixed access points. Instead of fixed antenna positions, ADAPT develops flexible, programmable radio units that can be dynamically positioned wherever reliable connectivity is needed.Integrated cybersecurity and tamper monitoring: 
  • Adaptive campus networks place special demands on security:  
    Systems that change autonomously must also be monitored autonomously. ADAPT is therefore developing integrated security mechanisms that secure the network throughout its entire lifecycle. Radio-based environmental validation continuously checks whether the network is operating according to the correct environmental model. 

This forms the basis for a campus network tool that supports the planning, operation, and further development of 5G/6G campus networks in production and intralogistics. 

Iterative Approach: From the PACE Lab to the Real Campus Network

ADAPT relies on an iterative development process:

Validation at the Fraunhofer IML PACE-Lab

The campus network tool is first tested in a laboratory environment at Fraunhofer IML. The PACE Lab features an O-RAN-based 5G campus network, a high-precision motion-capturing system, and various robotics platforms. There, digital twins, AI optimization, and campus network security can be tested and improved under controlled conditions. 

Testing in industrial environments

In the next step, ADAPT will be validated in the industrial environments of project partners KRONE and RHENUS. Here, the Campus Network Tool demonstrates how it can support 5G/6G campus network infrastructures under real-world conditions.

Transfer to other companies and industries

A project-accompanying committee with partners from associations such as VDMA and the Open Logistics Foundation facilitates the transfer of knowledge to other companies and sectors–ranging from agriculture and large-scale temporary events to the construction industry and healthcare. 

Operating campus networks efficiently, securely, and with future viability

ADAPT is creating a campus network tool that helps companies plan their 5G/6G campus networks: 

  • plan in a targeted and efficient manner (network planning) 
  • Optimize continuously and automatically 
  • Design them to be secure and resilient against attacks 
  • Adapt them flexibly to changing production and logistics scenarios 

In this way, campus networks become an active lever for efficiency, security, and cost optimization—from initial network planning through ongoing operations.

Funding

Funded by the ERDF/JTF Program NRW 2021–2027