AI Edge Cloud service provisioning for Knowledge Management Smart Applications

This paper investigates a serverless edge-cloud architecture to support knowledge management processes within smart cities,which align with the goals of Society 5.0 to create human-centered, data-driven urban environments. The proposed architectureleverages cloud computing for scalability and on-demand resource provisioning, and edge computing for cost-efficiency anddata processing closer to data sources, while also supporting serverless computing for simplified application development.Together, these technologies enhance the responsiveness and efficiency of smart city applications, such as traffic management,public safety, and infrastructure governance, by minimizing latency and improving data handling at scale. Experimentalanalysis demonstrates the benefits of deploying KM processes on this hybrid architecture, particularly in reducing datatransmission times and alleviating network congestion, while at the same time providing options for cost-efficient computations.In addition to that, the study also identifies the characteristics, opportunities and limitations of the edge and cloud environmentin terms of computation and network communication times. This architecture represents a flexible framework for advancingknowledge-driven services in smart cities, supporting further development of smart city applications in KM processes.