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

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.