When each railway operator independently deploys an on-premises local 5G network and introduces AI servers within its own railway network (local 5G base stations, core network, and AI servers), this leads to high upfront deployment costs and inefficiencies in AI training.
Both local 5G and AI often become major barriers in terms of deployment and operational costs. This challenge is even more pronounced for regional railway operators, which typically have more limited financial resources compared to urban rail operators.
Large-scale data collection and training are required to enhance the precision of AI detection. The tracks of each railway operator share the same components, such as rails, sleepers, and ballast. By sharing and learning from data collected across all operators, the AI model can be rapidly advanced, significantly improving anomaly detection accuracy.
Sharing a 5G Core among multiple railway operators significantly reduces the cost of deploying local 5G networks at each operator's stations and premises.
Thank you for shining a light on Sumitomo's unique Local 5G Core and AI Sharing Service. This method not only promises improved connectivity for train operators, but it also demonstrates the transformative power of localized technology solutions in public slope free transportation. As we go into the digital age, these innovations have the potential to greatly improve operational efficiency and passenger experience across a wide range of industries. Your insights are really useful!