The winning IS-Wireless proposal targets Pilot1’s scenario: remote control of cranes (RTGs) with augmented reality (AR) support. This pilot takes place in the port of Malta and requires low-latency and reliable wireless communication between remote operators, situated in the port offices, and a number of cranes (or other infrastructure) distributed across its area. In order for the operators to safely maneuver the RTGs (moving containers of cargo around the port) they need access to several high quality video streams of the RTGs’ surroundings with ca. 60Mb/s throughput per crane in the uplink direction. Sustaining such high throughput puts great pressure on the available 4G and WiFi networks, which tends to be filled by high capacity networks, i.e. 5G. Motivated by the above, IS-Wireless proposal focuses on deploying a virtual and disaggregated open-RAN 5G mobile network in the port office edge servers and on the cranes used in the project.
To achieve the end-goal of integrating a 5G solution with the architecture of Assist-IoT – the proposed project will deliver the key components of the O-RAN based 5G implementation as proprietary solution of IS-Wireless. This will consist of the following elements: radio units (RU), distributed unit (DU), centralised unit (CU), core network (CN) and RAN intelligent controller (RIC) and xApps.
With the innovation by IS-Wireless the ASSIST-IoT framework will be able to perform intelligent network bonding / switching between public 4G, WiFi and the proposed private 5G or utilising them concurrently with the goal of maximising the reliability and thus also QoE of the remote operators of the cranes in the marine port of Malaga.
We will perform research and integration works in order to deliver the improved reliability and video quality, noticeable to the operators and the port operation in general, generating less frustration in their work, potentially leading to longer duration of high focus periods.IS-Wireless innovation comprises the use of O-RAN based 5G disaggregated and virtualized network with optimization algorithms taking into account network metrics, video quality, resource availability or other measurable information to adapt the bonded network for maximising one or more objectives.