From Algorithm to Operation: A Scoping Review of Realization Conditions for Deploying Data-Driven Thermally Activated Building Systems

Thermally activated building systems offer significant potential for low-carbon building operation and energy flexibility by using building mass as distributed thermal storage. Recent advances in data-driven control, machine learning, and digital building infrastructure have expanded their technical capabilities. However, practical deployment remains limited. This paper addresses that gap through a scoping review of the literature on data-driven thermally activated building systems, with a focus on the conditions required for implementation, integration, and sustained operation in practice. The review examines publication patterns, realization stages, dominant realization pathways, and recurring enablers and barriers across the field. The results show that the literature is concentrated in conceptual, simulation, and pilot-stage studies, while evidence of long-term operation in occupied buildings remains scarce and evidence of scalable or transferable realization in the reviewed TABS literature remains limited. The paper proposes five realization conditions for deployment as an interpretive synthesis of the reviewed literature: operational observability, deployable model architecture, embedded digital integration, operational acceptability, and organizational handover capacity. The review reframes data-driven thermally activated building systems as a realization challenge rather than only a control problem and provides a structured analytical framework to support future research and deployment-oriented evaluation in energy informatics.