Vicente Botti

This paper proposes a noise-aware, iterative methodology for enriching an initial mobility clustering through the sequential addition of explanatory variables. The framework separates one-off density-based cluster discovery from scalable characterisation over a fixed analytical population. Candidate variables are retained only when they improve the predefined distributional criteria and preserve continuity with the latest accepted partition. Evaluation on a large sensing-based mobility dataset from Valencia shows that the proposed architecture supports scalable and auditable explanatory enrichment while keeping the observation set unchanged and explicitly separating distributional admissibility from inter-partition continuity.

In this paper, we introduce SPADE, a framework engineered for building Digital Twins through Multi-Agent Systems. The architecture is inherently scalable and distributed, aligning perfectly with the demands of modern Digital Twin environments. We implement the Agents and Artifacts meta-model via the SPADE Artifacts extension, which serves as a structured interface connecting autonomous agents with their physical system counterparts. To demonstrate the framework’s efficacy, we detail a case study involving urban traffic management in Valencia, Spain. In this implementation, we model 386 street segments as individual agents responsible for managing traffic flows and coordinating redistribution efforts. The research delineates a MAS-based communication strategy spanning the entire network and introduces a consensus algorithm specifically designed to manage traffic rerouting when a street is closed. Finally, we present results from a series of experimental trials and evaluate the system’s broader potential. By synthesizing diverse data sources and providing an interactive dashboard for visualizing network conditions, this work demonstrates how SPADE can serve as a robust foundation for Digital Twin development, illustrating its potential for real-world urban applications through a conceptual implementation grounded in open sensor data.