The sustainable management and valorisation of heritage assets increasingly require digital infrastructures able to combine efficiency, inclusiveness, and resilience. Current heritage conservation and tourism logistics often suffer from fragmentation, limited interoperability across institutions, and insufficient real-time monitoring. This paper proposes an Urban Physical Internet (U-PI) architecture that applies principles of modularity, openness, and interoperability to the heritage domain, integrating Edge AI, Federated Learning, and Digital Twins. At the edge layer, lightweight AI models deployed on IoT devices monitor flows of visitors, environmental conditions, and energy usage within cultural venues and heritage sites. The federated learning layer enables museums, municipalities, and SMEs in the tourism ecosystem to collaboratively train predictive models without sharing sensitive raw data, thus ensuring privacy and respecting intellectual property. The digital twin layer provides a virtual representation of urban districts and heritage infrastructures, allowing scenario-based simulations to optimise visitor mobility, energy demand, and resilience strategies. Preliminary simulations indicate that the proposed U-PI approach can reduce congestion in high-traffic heritage districts, lower energy consumption of buildings, and improve the equitable distribution of cultural services among large institutions and smaller local actors. In addition, blockchain-based event logs and urban data spaces ensure transparent governance and auditability of heritage-related transactions. The contribution situates heritage management within broader sustainability transitions, aligning with European Green Deal goals and national strategies on digitalisation and cultural innovation. By embedding resilience and fairness at architectural level, the proposed framework offers a roadmap for safer, smarter, and more accessible heritage ecosystems.
Leveraging the urban physical internet for sustainable heritage management: Edge AI, federated learning, and digital twins
Fabrizio BenelliWriting – Review & Editing
;Franco MaciarielloWriting – Review & Editing
2025-01-01
Abstract
The sustainable management and valorisation of heritage assets increasingly require digital infrastructures able to combine efficiency, inclusiveness, and resilience. Current heritage conservation and tourism logistics often suffer from fragmentation, limited interoperability across institutions, and insufficient real-time monitoring. This paper proposes an Urban Physical Internet (U-PI) architecture that applies principles of modularity, openness, and interoperability to the heritage domain, integrating Edge AI, Federated Learning, and Digital Twins. At the edge layer, lightweight AI models deployed on IoT devices monitor flows of visitors, environmental conditions, and energy usage within cultural venues and heritage sites. The federated learning layer enables museums, municipalities, and SMEs in the tourism ecosystem to collaboratively train predictive models without sharing sensitive raw data, thus ensuring privacy and respecting intellectual property. The digital twin layer provides a virtual representation of urban districts and heritage infrastructures, allowing scenario-based simulations to optimise visitor mobility, energy demand, and resilience strategies. Preliminary simulations indicate that the proposed U-PI approach can reduce congestion in high-traffic heritage districts, lower energy consumption of buildings, and improve the equitable distribution of cultural services among large institutions and smaller local actors. In addition, blockchain-based event logs and urban data spaces ensure transparent governance and auditability of heritage-related transactions. The contribution situates heritage management within broader sustainability transitions, aligning with European Green Deal goals and national strategies on digitalisation and cultural innovation. By embedding resilience and fairness at architectural level, the proposed framework offers a roadmap for safer, smarter, and more accessible heritage ecosystems.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

