This paper presents the deployment and evaluation of the SENNSE platform, an IoT-based solution combining distributed environmental sensors and 3D digital twin integration. SENNSE was implemented in the Grotta degli Animali, a semiconfined 16th-century grotto in Florence, Italy. The platform continuously monitored temperature, humidity, enabling spatially contextualized data analysis through immersive visualization. Exploratory analysis revealed zone-specific microclimatic responses, and there were remarkable humidity responses to water activation in the Lion tub, emphasizing the need for adaptive, localized conservation measures. SENNSE demonstrates how realtime sensing, linked to interactive spatial models, can enhance conservation decision-making and support proactive heritage management.
Real-time environmental monitoring in historical semiconfined spaces: A case study of the SENNSE IoT deployment in Florence / Muci, Irene; Bucciero, Alberto; Chirivì, Alessandra; Colella, Riccardo; Emara, Mohamed; Greco, Matteo; Ali Jaziri, Mohamed; Pandurino, Andrea; Riminesi, Cristiano; Santo Sabato, Stefano; Taurino, Francesco; Zecca, Davide; Tucci, Grazia; Castellini, Marta; Conti, Alessandro; Fiorini, Lidia. - (2025). (Intervento presentato al convegno SOFTCOM tenutosi a Split HR).
Real-time environmental monitoring in historical semiconfined spaces: A case study of the SENNSE IoT deployment in Florence
Irene Muci;Lidia Fiorini
2025
Abstract
This paper presents the deployment and evaluation of the SENNSE platform, an IoT-based solution combining distributed environmental sensors and 3D digital twin integration. SENNSE was implemented in the Grotta degli Animali, a semiconfined 16th-century grotto in Florence, Italy. The platform continuously monitored temperature, humidity, enabling spatially contextualized data analysis through immersive visualization. Exploratory analysis revealed zone-specific microclimatic responses, and there were remarkable humidity responses to water activation in the Lion tub, emphasizing the need for adaptive, localized conservation measures. SENNSE demonstrates how realtime sensing, linked to interactive spatial models, can enhance conservation decision-making and support proactive heritage management.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


