In modern digital ecosystems, managing heterogeneous data sources is a significant challenge, particularly within Renewable Energy Communities (RECs), where multiple energy vectors, such as electricity, heating, and water, must be integrated seamlessly. The GAIA meta-platform addresses the persistent fragmentation of IoT ecosystems by enabling federated access, semantic harmonization, and cross-domain analytics across heterogeneous data silos. Designed to support both expert and non-expert users, GAIA combines modular data processing, a Python SDK, and an AI-driven conversational agent (i.e., GAIA Chat) to facilitate intuitive interaction with multi-source datasets. This paper presents the platform’s architecture and functionalities, emphasizing its role in advancing data-driven services for RECs. Finally, a real-world deployment demonstrates GAIA’s ability to integrate energy and water data, enabling advanced use cases such as cross-domain anomaly detection and indirect consumption estimation. The results validate GAIA as a scalable, domain-agnostic infrastructure capable of supporting intelligent services in complex smart environments.

From Fragmented Data to Smart Conversations in Energy Communities: The GAIA Approach to Cross-Domain IoT Integration / Viticchié, Alessio; Cetrone, Felice; Puntorieri, Roberto; Camarda, Christian; Napoli, Leonardo; Patti, Edoardo; Aliberti, Alessandro. - ELETTRONICO. - (In corso di stampa). (Intervento presentato al convegno 25th EEEIC International Conference on Environment and Electrical Engineering (EEEIC) tenutosi a Chania, Crete nel 15-18 July, 2025).

From Fragmented Data to Smart Conversations in Energy Communities: The GAIA Approach to Cross-Domain IoT Integration

Roberto Puntorieri;Christian Camarda;Edoardo Patti;Alessandro Aliberti
In corso di stampa

Abstract

In modern digital ecosystems, managing heterogeneous data sources is a significant challenge, particularly within Renewable Energy Communities (RECs), where multiple energy vectors, such as electricity, heating, and water, must be integrated seamlessly. The GAIA meta-platform addresses the persistent fragmentation of IoT ecosystems by enabling federated access, semantic harmonization, and cross-domain analytics across heterogeneous data silos. Designed to support both expert and non-expert users, GAIA combines modular data processing, a Python SDK, and an AI-driven conversational agent (i.e., GAIA Chat) to facilitate intuitive interaction with multi-source datasets. This paper presents the platform’s architecture and functionalities, emphasizing its role in advancing data-driven services for RECs. Finally, a real-world deployment demonstrates GAIA’s ability to integrate energy and water data, enabling advanced use cases such as cross-domain anomaly detection and indirect consumption estimation. The results validate GAIA as a scalable, domain-agnostic infrastructure capable of supporting intelligent services in complex smart environments.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3002717