CampusDynA

Dynamic adaptation of campus networks and applications in industrial usage scenarios

© Project CampusDynA

Project description
CampusDynA aims to realise applications in the fields of autonomous mobile robotics, resource efficiency of production facilities and civil security of production sites with the help of open 5G campus networks and thus contributes to the evaluation of the concrete added value of this technology for industrial usage scenarios, which is critical for user acceptance. The focus is on aspects of the mutual dynamic adaptation of network and usage behaviour (see Use Cases). The implications for performance increases and innovations on both the user and provider side are analysed, as are the effects on society as a whole (sustainability, civil security).

Market perspective and product promise
The OpenRAN approach offers the potential for a restructuring of communication systems or the creation of a market for new communication solutions and thus equally for their applications. The open, standardised interfaces and the consistent virtualisation not only of the OpenRAN components but also of the application components enable time and resource savings and thus a high level of acceptance for campus networks and their applications. The three application scenarios also show the broad application possibilities based on dynamic network parameters and the potential for significant unique selling points. Consequently, a strong demand-oriented market perspective with significant market influence, broad penetration and increased broad impact can be assumed for the object of the project proposal. In addition, the project results should also contribute to the consideration of perspective regulatory requirements for the network operators, in that the campus networks should actively support the management of damage events.

The participating companies intend to actively develop the developed concept further after the funding and thus ensure a continuation of the project results. Gestalt Robotics and T-Systems each have application-oriented product portfolios into which OpenRAN-based capabilities can be seamlessly integrated as competitive differentiating features. For OSRAM, this opens up opportunities for process and resource optimisation, which can, among other things, reduce operating costs and thus also flow into the investment planning for campus networks. By embedding the project in the network of the Werner von Siemens Centre for Industry and Science at the Siemensstadt site in Berlin, we are promoting the creation of an ecosystem for 5G campus networks and the exchange with industry and other research projects.

Challenge and innovation
Dynamic changes in network requirements can usually hardly be taken into account in current campus network solutions without cost-driving overprovisioning. For example, new types of edge-controlled automated guided vehicles (AGVs) with a large bandwidth requirement (examined here as scenario S1) would not be able to be realised by established methods for network design: An assumed, even distribution of autonomous mobile robots in the area contradicts reality with an increasing trend towards flexible manufacturing, whereby local areas with over- or under-coverage will occur and the overall system is thus no longer usable. In turn, campus-wide provision of capacity for AGVs blocks spectrum for other, neighbouring users and is not economically feasible. S1 is intended to significantly extend the limits of the previous bandwidth restriction through its spatially flexible allocation in the campus network.

In addition to the spatio-temporal dynamics of bandwidth demand, there are also comparable dynamics with regard to latency in the network. This will be investigated in a second scenario (S2). Due to the restructuring of electricity generation in the Federal Republic of Germany, large consumers will increasingly have to contribute to grid stabilisation, which means that the maximum (peak) power that can be called up can be planned for ever smaller periods of time. At the same time, the increasing flexibility of production is also changing the location of the largest consumers on campus. In order not to provoke any economic failures, it will therefore be unavoidable to monitor these decentralised large consumers in real time and to feed them back with a system for optimising energy use, so that production failures due to energy poverty cannot occur in the first place. Within S2, a dynamic regulation of the network latency is to be realised so that critical system areas and process phases within the campus network can be detected in real time and readjusted by artificial intelligence.

The third application scenario (S3) is intended to expand the previously mentioned applications to include the aspect of availability for prioritised use by third parties. In the event of a major incident caused by an accident or a hazardous materials accident in an industrial plant, a rapid response is urgently required to avert serious effects on people and the environment. Currently, this leads to the (partial) evacuation of the site and the dispatch of rescue forces followed by recovery forces, which have to build up their own communication and data infrastructures. While regular operations are at least partially halted, the campus network infrastructure already in place would currently lie largely unused. If this infrastructure could be made available to emergency forces quickly and easily, e.g. for the use of reconnaissance robots or drones, a decisive contribution to saving lives can be made.

Challenges:
Spatio-temporal dynamics of bandwidth demand, dynamics of latency requirements on the network, network availability for prioritised use by third parties.Innovationen:
Flexible, bedarfsorientierte Bandbreitenallokation für die netzgestützte Steuerung fahrerloser Transportsysteme, Netzgestützte Echtzeitüberwachung und Energieeinsatzoptimierung für elektrische Großverbraucher in der Fertigung, Einfache Integration von neuen Netzteilnehmern, um schnelle Reaktionen auf Großschadensereignisse zu ermöglichen.

Innovations:
Flexible, demand-based bandwidth allocation for network-based control of driverless transport systems, Network-based real-time monitoring and energy use optimisation for large-scale electrical consumers in manufacturing, Easy integration of new network subscribers to enable rapid responses to large-scale incidents.

Use Cases

Consortium
Gestalt Robotics GmbH (GR), T-Systems International GmbH (TSI), OSRAM GmbH, Fraunhofer IOSB (IOSB), Fraunhofer IPK (IPK), WvSC e.V. (WvSC)

Duration
April 2022 – März 2025

Budget
Total funds: 4.0 million €
Funding amount: 2.8 million €